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Isis 3.0 Object Programmers' Reference |
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#include <Gruen.h>
Inheritance diagram for Isis::Gruen:
This class provides adaptive image (chip) registration using the AutoReg factory architecture. This algorithm uses an Affine transform to iteratively adjust the search chip at each iteration. Each iteration solves for new adjustments to the Affine transform until the 6 affine parameters fall below the tolerances as specified in AffineThreshHold1 and AffineThreshHold2.
This class minimizes the 6 specifiable Affine transform components of a 3x3 matrix. The three Affine components for X (sample) and Y (line) are scale, shear and translation. Gruen provides control over the maximum values these three components should attain in order for the registration to converge to a successful match. These limits are specified by AffineScaleTolerance, AffineShearTolerance and AffineTranslationTolerance. AffineShearTolerance is optional and if not specified, it defaults to the value of AffineScaleTolerance. These tolerances specify the maximum amount of translation pixels can be shifted between one Gruen iteration and another. For example, AffineTranslationTolerance = 0.2 means that a subsearch chip cannot move in sample or line direction more than 0.2 pixels in order to satisfy convergence. AffineScaleTolerance constrains the sample and line scale elements of the Affine transformation. And AffineShearTolerance constrains the sample and line shear elements of the Affine transformation. The scale and shear parameters are scaled by size of the Chip. The sample scale and shear Affine components maximum limit is computed as AffineScaleTolerance/((Samples-1)/2) and AffineShearTolerance/((Samples-1)/2). Likewise, the line scale and shear maximums are computed using Lines in the preceding equation.
For internal use only.
Definition at line 83 of file Gruen.h.
Public Types | |
| Success | |
| Success. | |
| PatternChipNotEnoughValidData | |
| Not enough valid data in pattern chip. | |
| FitChipNoData | |
| Fit chip did not have any valid data. | |
| FitChipToleranceNotMet | |
| Goodness of fit tolerance not satisfied. | |
| SurfaceModelNotEnoughValidData | |
| Not enough points to fit a surface model for sub-pixel accuracy. | |
| SurfaceModelSolutionInvalid | |
| Could not model surface for sub-pixel accuracy. | |
| SurfaceModelDistanceInvalid | |
| Surface model moves registration more than one pixel. | |
| PatternZScoreNotMet | |
| Pattern data max or min does not pass the z-score test. | |
| SurfaceModelEccentricityRatioNotMet | |
| Ellipse eccentricity of the surface model not satisfied. | |
| AdaptiveAlgorithmFailed | |
| Error occured in Adaptive algorithm. | |
| enum | RegisterStatus { Success, PatternChipNotEnoughValidData, FitChipNoData, FitChipToleranceNotMet, SurfaceModelNotEnoughValidData, SurfaceModelSolutionInvalid, SurfaceModelDistanceInvalid, PatternZScoreNotMet, SurfaceModelEccentricityRatioNotMet, AdaptiveAlgorithmFailed } |
Public Member Functions | |
| Gruen (Pvl &pvl) | |
| Basic Gruen algorithm constructor. | |
| virtual | ~Gruen () |
| Destructor. | |
| virtual bool | IsAdaptive () |
| Gruen default mode is adaptive. | |
| double | Gain () const |
| Returns the radiometric gain value from the last solution. | |
| double | Shift () const |
| Returns the radiometric shift value from the last solution. | |
| void | SetRadiometrics (const double &gain=0.0, const double &shift=0.0) |
| Sets established radiometric parameters for registration processes. | |
| double | SpiceTolerance () const |
| Returns the SPICE tolerance constraint as read from config file. | |
| double | AffineTolerance () const |
| Returns the Affine tolerance constraint as read from config file. | |
| GruenResult | algorithm (Chip &pattern, Chip &subsearch) |
| Real workhorse of the computational Gruen algorithm. | |
| const GruenResult & | Results () const |
| Returns the results container from the last solution. | |
| bool | IsGood () const |
| Returns status of the last registration result. | |
| bool | IsGood (const GruenResult &result) const |
| Returns the status of the given Gruen result container. | |
| Chip * | PatternChip () |
| Return pointer to pattern chip. | |
| Chip * | SearchChip () |
| Return pointer to search chip. | |
| Chip * | FitChip () |
| Return pointer to search chip. | |
| Chip * | ReducedPatternChip () |
| Return pointer to reduced pattern chip. | |
| Chip * | ReducedSearchChip () |
| Return pointer to reduced search chip. | |
| Chip * | ReducedFitChip () |
| Return pointer to reduced fix chip. | |
| void | SetSubPixelAccuracy (bool on) |
| If the sub-accuracy is enable the Register() method will attempt to match the pattern chip to the search chip at sub-pixel accuracy, otherwise it will be registered at whole pixel accuracy. | |
| void | SetPatternValidPercent (const double percent) |
| Set the amount of data in the pattern chip that must be valid. | |
| void | SetTolerance (double tolerance) |
| Set the tolerance for an acceptable goodness of fit. | |
| void | SetSurfaceModelWindowSize (int size) |
| Set the surface model window size. | |
| void | SetSurfaceModelDistanceTolerance (double distance) |
| Set a distance the surface model solution is allow to move away from the best whole pixel fit in the fit chip. | |
| void | SetReductionFactor (int reductionFactor) |
| Set the reduction factor used to speed up the pattern matching algorithm. | |
| void | SetPatternZScoreMinimum (double minimum) |
| Set the minimum pattern zscore. | |
| void | SetSurfaceModelEccentricityRatio (double ratioTolerance) |
| A 1:1 ratio represents a perfect circle. | |
| double | PatternValidPercent () const |
| Return pattern valid percent. | |
| double | Tolerance () const |
| Return match algorithm tolerance. | |
| AutoReg::RegisterStatus | Register () |
| Walk the pattern chip through the search chip to find the best registration. | |
| double | GoodnessOfFit () const |
| Return the goodness of fit of the match algorithm. | |
| bool | IsIdeal (double fit) |
| double | ChipSample () const |
| Return the search chip sample that best matched. | |
| double | ChipLine () const |
| Return the search chip line that best matched. | |
| double | CubeSample () const |
| Return the search chip cube sample that best matched. | |
| double | CubeLine () const |
| Return the search chip cube line that best matched. | |
| void | ZScores (double &score1, double &score2) const |
| Return the ZScores of the pattern chip. | |
| Pvl | RegistrationStatistics () |
| This returns the cumulative registration statistics. | |
| PvlGroup | RegTemplate () |
| This function returns the keywords that this object was created from. | |
Protected Types | |
| typedef GSL::GSLUtility::GSLMatrix | GSLMatrix |
| typedef GSL::GSLUtility::GSLVector | GSLVector |
Protected Member Functions | |
| virtual std::string | AlgorithmName () const |
| Returns the default name of the algorithm as Gruen. | |
| bool | solve (GruenResult &result) |
| Computes solution and error analysis using Cholesky/Jacobi methods. | |
| virtual double | MatchAlgorithm (Chip &pattern, Chip &subsearch) |
| Minimization of data set using Gruen algorithm. | |
| virtual bool | CompareFits (double fit1, double fit2) |
| This virtual method must return if the 1st fit is equal to or better than the second fit. | |
| virtual double | IdealFit () const |
| Returns the ideal fit for a perfect Gruen result. | |
| virtual AutoReg::RegisterStatus | AdaptiveRegistration (Chip &sChip, Chip &pChip, Chip &fChip, int startSamp, int startLine, int endSamp, int endLine, int bestSamp, int bestLine) |
| Applies the adaptive Gruen algorithm to pattern and search chips. | |
| virtual Pvl | AlgorithmStatistics (Pvl &pvl) |
| Create Gruen error and processing statistics Pvl output. | |
| void | SetChipSample (double sample) |
| Sets the search chip subpixel sample that matches the pattern tack sample. | |
| void | SetChipLine (double line) |
| Sets the search chip subpixel line that matches the pattern tack line. | |
| void | SetGoodnessOfFit (double fit) |
| Sets the goodness of fit for adaptive algorithms. | |
| void | Parse (Pvl &pvl) |
| Initialize parameters in the AutoReg class using a PVL specification. | |
| bool | ModelSurface (std::vector< double > &x, std::vector< double > &y, std::vector< double > &z) |
| We will model a 2-d surface as:. | |
| Chip | Reduce (Chip &chip, int reductionFactor) |
| This method reduces the given chip by the given reduction factor. | |
Protected Attributes | |
| PvlObject | p_template |
| AutoRegistration object that created this projection. | |
Private Types | |
| typedef CollectorMap< int, ErrorCounter > | ErrorList |
| Declaration of error count list. | |
| NotEnoughPoints = 1 | |
| CholeskyFailed = 2 | |
| EigenSolutionFailed = 3 | |
| AffineNotInvertable = 4 | |
| MaxIterationsExceeded = 5 | |
| RadShiftExceeded = 6 | |
| RadGainExceeded = 7 | |
| MaxEigenExceeded = 8 | |
| AffineDistExceeded = 9 | |
| enum | GruenErrors { NotEnoughPoints = 1, CholeskyFailed = 2, EigenSolutionFailed = 3, AffineNotInvertable = 4, MaxIterationsExceeded = 5, RadShiftExceeded = 6, RadGainExceeded = 7, MaxEigenExceeded = 8, AffineDistExceeded = 9 } |
| Error enumeration values. More... | |
Private Member Functions | |
| template<typename T> | |
| T | ConfKey (const DbProfile &conf, const std::string &keyname, const T &defval, int index=0) const |
| Helper method to initialize parameters. | |
| template<typename T> | |
| PvlKeyword | ParameterKey (const std::string &keyname, const T &value, const std::string &unit="") const |
| Keyword formatter for Gruen parameters. | |
| PvlKeyword | ValidateKey (const std::string keyname, const double &value, const std::string &unit="") const |
| Checks value of key, produces appropriate value. | |
| ErrorList | initErrorList () const |
| Creates an error list from know Gruen errors. | |
| void | logError (int gerrno, const std::string &gerrmsg) |
| Logs a Gruen error. | |
| PvlGroup | StatsLog () const |
| Create a PvlGroup with the Gruen specific statistics. | |
| PvlGroup | ParameterLog () const |
| Create a PvlGroup with the Gruen specific parameters. | |
| void | init (Pvl &pvl) |
| Initialize the object. | |
| double | getDefaultGain () const |
| Returns the default radiometric gain value. | |
| double | getDefaultShift () const |
| Returns the default radiometric shift value. | |
| void | reset () |
| Reset registration-dependant counters only. | |
| void | resetStats () |
| Reset Gruen statistics as needed. | |
| GSLVector | getThreshHold (const Chip &chip) const |
| Compute the Affine convergence parameters. | |
| bool | HasConverged (const GSLVector &alpha, const GSLVector &thresh, const GruenResult &results) const |
| Tests Affine parameters for convergence. | |
| BigInt | MinValidPoints (BigInt totalPoints) const |
| Computes the number of minimum valid points. | |
| bool | ValidPoints (BigInt totalPoints, BigInt nPoints) const |
| Determines if number of points is valid percentage of all points. | |
| void | ErrorAnalysis (GruenResult &result) |
| Computes/determines error analysis after the solution converges. | |
| bool | TestConstraints (const bool &done, GruenResult &result) |
| Test user limits/contraints after the algorithm has converged. | |
| Affine | UpdateAffine (GruenResult &result, const Affine >rans) |
| Updates the affine transform with the final iterative solution. | |
| void | UpdateChip (Chip &sChip, const Affine &affine) |
| Updates the (search) chip with the final Affine transform. | |
| bool | CheckAffineTolerance () |
| Check affine tolerance for validity. | |
| AutoReg::RegisterStatus | Status (const GruenResult &result) const |
| Returns the proper status given a Gruen result container. | |
| AutoReg::RegisterStatus | Status () const |
| Returns status of the last Gruen registration result. | |
Private Attributes | |
| DbProfile | _prof |
| int | _maxIters |
| double | _transTol |
| double | _scaleTol |
| double | _shearTol |
| double | _affineTol |
| double | _spiceTol |
| double | _rgainMinTol |
| double | _rgainMaxTol |
| double | _rshiftTol |
| double | _fitChipScale |
| int | _nIters |
| GruenResult | _result |
| last result, cummulative | |
| BigInt | _totalIterations |
| ErrorList | _errors |
| BigInt | _unclassified |
| double | _defGain |
| double | _defShift |
| Statistics | _eigenStat |
| Statistics | _iterStat |
| Statistics | _shiftStat |
| Statistics | _gainStat |
Classes | |
| struct | ErrorCounter |
| Structure that maintains error counts. More... | |
typedef CollectorMap<int, ErrorCounter> Isis::Gruen::ErrorList [private] |
enum Isis::Gruen::GruenErrors [private] |
enum Isis::AutoReg::RegisterStatus [inherited] |
| Isis::Gruen::Gruen | ( | Pvl & | pvl | ) |
Basic Gruen algorithm constructor.
This will construct a minimum difference search algorith. It is recommended that you use a AutoRegFactory class as opposed to this constructor
| pvl | A Pvl object that contains a valid automatic registration definition |
| virtual Isis::Gruen::~Gruen | ( | ) | [inline, virtual] |
| AutoReg::RegisterStatus Isis::Gruen::AdaptiveRegistration | ( | Chip & | sChip, | |
| Chip & | pChip, | |||
| Chip & | fChip, | |||
| int | startSamp, | |||
| int | startLine, | |||
| int | endSamp, | |||
| int | endLine, | |||
| int | bestSamp, | |||
| int | bestLine | |||
| ) | [protected, virtual] |
Applies the adaptive Gruen algorithm to pattern and search chips.
This method computes the adaptive Gruen algorithm for a pattern chip and search chip. The search chip is assumed to be of a larger size than the pattern chip as dictated by the contents of the registration definition file.
This algorithm can be used with or without "fast geoming" the search chip. It works quite well where the two images are assumed to be nearly spatially registered. Its real intent is to compute parallax angles between two images taken at different viewing geometry. This provides an efficient process for deriving a digital elevation model (DEM) from two datasets.
The Gruen algorithm is applied to the chips until the algorithm converges (current iteration yields a detla affine within tolerance limits), an error is encountered, or the maximum number of iterations is exceeded.
Note that bestSamp and bestLine may not be the original center of the search chip. It is subject to chip reduction matching as specified by the user. All distance tolerances are compute from this postion. The process of chip reduction processing is handled by AutoReg prior to calling this routine.
| sChip | Full search chip as rendered from the search image | |
| pChip | Full pattern chip as rendered from the pattern/match image | |
| fChip | Maintains the solution vector at each chip location | |
| startSamp | Starting sample of the search image range | |
| startLine | Starting line of the search image range | |
| endSamp | Ending sample of the search image range | |
| endLine | Ending line of the search image range | |
| bestSamp | Best registering sample of search chip | |
| bestLine | best registering line of search chip |
Reimplemented from Isis::AutoReg.
Definition at line 359 of file Gruen.cpp.
References _fitChipScale, _maxIters, _nIters, _result, algorithm(), Isis::GruenResult::Alpha(), CheckAffineTolerance(), Isis::Chip::ChipLine(), Isis::Chip::ChipSample(), Isis::iException::Clear(), Isis::GruenResult::Constraints(), Isis::Chip::CubeLine(), Isis::Chip::CubeSample(), Isis::GruenResult::Eigen(), ErrorAnalysis(), Isis::Chip::Extract(), Isis::GruenResult::gerrmsg, Isis::GruenResult::gerrno, getThreshHold(), Isis::Chip::getTransform(), HasConverged(), Isis::GruenResult::isGood, Isis::GruenResult::IsGood(), Isis::Chip::IsInsideChip(), Isis::Chip::Lines(), logError(), Isis::Null, reset(), Isis::Chip::Samples(), Isis::Affine::Scale(), Isis::Chip::SetAllValues(), Isis::AutoReg::SetChipLine(), Isis::Chip::SetChipPosition(), Isis::AutoReg::SetChipSample(), Isis::GruenResult::setChipTransform(), Isis::Chip::SetCubePosition(), Isis::GruenResult::setFinalImage(), Isis::AutoReg::SetGoodnessOfFit(), Isis::Chip::SetSize(), Isis::GruenResult::setStartImage(), Isis::Chip::setTransform(), Isis::Chip::SetValue(), ss, Status(), Isis::Chip::TackLine(), Isis::Chip::TackSample(), TestConstraints(), Isis::Affine::Translate(), UpdateAffine(), UpdateChip(), and Isis::Chip::Write().
| double Isis::Gruen::AffineTolerance | ( | ) | const [inline] |
Returns the Affine tolerance constraint as read from config file.
Definition at line 116 of file Gruen.h.
References _affineTol.
Referenced by CheckAffineTolerance().
| GruenResult Isis::Gruen::algorithm | ( | Chip & | pattern, | |
| Chip & | subsearch | |||
| ) |
Real workhorse of the computational Gruen algorithm.
This method is called for all registration requests and actually performs the registration of two chips.
The pattern chip is deemed constant. The subsearch chip is generally an extraction from the search chip that has had an affine transform applied to fill it.
At each iteration of the Gruen algorithm, the affine transform is incrementally updated based upon the results from this method. There are six affine parameters and two radiometric (shift and gain) parameters that are solved/computed here.
The algorithm itself is a first derivative computation of the subsearch chip with small radiometric adjustments applied to better tone match the two chips. This is intended to minimize the affine variability.
| pattern | Fixed pattern chip which subsearch is trying to match | |
| subsearch | Affined extraction of the search chip |
Definition at line 101 of file Gruen.cpp.
References _nIters, _totalIterations, a, Isis::GruenResult::ata, Isis::GruenResult::atl, Gain(), Isis::GruenResult::gerrmsg, Isis::GruenResult::gerrno, Isis::Chip::GetValue(), Isis::GruenResult::isGood, Isis::Chip::IsValid(), line, Isis::Chip::Lines(), logError(), MinValidPoints(), Isis::GruenResult::nIters, Isis::GruenResult::npts, Isis::GruenResult::resid, Isis::Chip::Samples(), Shift(), solve(), Isis::Chip::TackLine(), Isis::Chip::TackSample(), and ValidPoints().
Referenced by AdaptiveRegistration(), and MatchAlgorithm().
| virtual std::string Isis::Gruen::AlgorithmName | ( | ) | const [inline, protected, virtual] |
Returns the default name of the algorithm as Gruen.
Implements Isis::AutoReg.
Reimplemented in Isis::AdaptiveGruen.
Definition at line 132 of file Gruen.h.
Referenced by AlgorithmStatistics().
Create Gruen error and processing statistics Pvl output.
This method generates two groups specific to the Gruen algorithm: The GruenFailures group which logs all the errors enountered during processing and the GruenStatistics group which logs selected statistics gathered during a registration run.
These groups are added to the AutoReg log output Pvl container for reporting to user/log files.
Reimplemented from Isis::AutoReg.
Definition at line 479 of file Gruen.cpp.
References _errors, _unclassified, AlgorithmName(), e, Isis::CollectorMap< K, T, ComparePolicy, RemovalPolicy, CopyPolicy >::getNth(), IsAdaptive(), ParameterLog(), pvl(), Isis::CollectorMap< K, T, ComparePolicy, RemovalPolicy, CopyPolicy >::size(), and StatsLog().
| bool Isis::Gruen::CheckAffineTolerance | ( | ) | [private] |
Check affine tolerance for validity.
This method checks for a convergent solution that travels to far from the original tack point (best point in most cases). The user can control this tolerance with the AffineTolerance parameter in the registration config file. The check is a sample/line magnitude check from the original starting pixel location to the one after the affine transform has converged to match to a new cube pixel coordinate.
Note this check is independant of TestConstraints() method since the update of the chip only occurs after other limits pass. The chip must be updated and the new tack point cube pixel location must be determined prior to calling this method.
Definition at line 949 of file Gruen.cpp.
References _result, AffineTolerance(), Isis::GruenResult::ErrorMagnitude(), Isis::GruenResult::gerrmsg, Isis::GruenResult::gerrno, Isis::GruenResult::isGood, and logError().
Referenced by AdaptiveRegistration().
| double Isis::AutoReg::ChipLine | ( | ) | const [inline, inherited] |
Return the search chip line that best matched.
Definition at line 183 of file AutoReg.h.
References Isis::AutoReg::p_chipLine.
| double Isis::AutoReg::ChipSample | ( | ) | const [inline, inherited] |
Return the search chip sample that best matched.
Definition at line 180 of file AutoReg.h.
References Isis::AutoReg::p_chipSample.
| bool Isis::Gruen::CompareFits | ( | double | fit1, | |
| double | fit2 | |||
| ) | [protected, virtual] |
This virtual method must return if the 1st fit is equal to or better than the second fit.
| fit1 | 1st goodness of fit | |
| fit2 | 2nd goodness of fit |
Reimplemented from Isis::AutoReg.
| T Isis::Gruen::ConfKey | ( | const DbProfile & | conf, | |
| const std::string & | keyname, | |||
| const T & | defval, | |||
| int | index = 0 | |||
| ) | const [inline, private] |
Helper method to initialize parameters.
This method will check the existance of a keyword and extract the value
if it exists to the passed parameter (type). If it doesn't exist, the default values is returned.
| T | Templated variable type | |
| conf | Parameter profile container | |
| keyname | Name of keyword to get a value from | |
| defval | Default value it keyword/value doesn't exist | |
| index | Optional index of the value for keyword arrays |
Definition at line 230 of file Gruen.h.
References Isis::DbProfile::count(), Isis::DbProfile::exists(), value, and Isis::DbProfile::value().
Referenced by init().
| double Isis::AutoReg::CubeLine | ( | ) | const [inline, inherited] |
Return the search chip cube line that best matched.
Definition at line 189 of file AutoReg.h.
References Isis::AutoReg::p_cubeLine.
Referenced by Qisis::ControlPointEdit::registerPoint().
| double Isis::AutoReg::CubeSample | ( | ) | const [inline, inherited] |
Return the search chip cube sample that best matched.
Definition at line 186 of file AutoReg.h.
References Isis::AutoReg::p_cubeSample.
Referenced by Qisis::ControlPointEdit::registerPoint().
| void Isis::Gruen::ErrorAnalysis | ( | GruenResult & | result | ) | [private] |
Computes/determines error analysis after the solution converges.
This method maintains the error analysis computed from the Gruen algorithm when a convergent condition is encountered. This essentially is a copy of the iterative analysis that takes place at each application of the Gruen algorithm. It ensures the error analysis is current by making a copy of the last error analysis perform as found in the results container.
It moves the iterative error analysis to the cummulative result container.
| result | Iterative solution container with last error analysis that is to be preserved |
Definition at line 804 of file Gruen.cpp.
References _result, and Isis::GruenResult::setErrorAnalysis().
Referenced by AdaptiveRegistration().
| Chip* Isis::AutoReg::FitChip | ( | ) | [inline, inherited] |
Return pointer to search chip.
Definition at line 146 of file AutoReg.h.
References Isis::AutoReg::p_fitChip.
Referenced by Qisis::ControlPointEdit::saveChips().
| double Isis::Gruen::Gain | ( | ) | const [inline] |
Returns the radiometric gain value from the last solution.
Definition at line 106 of file Gruen.h.
References _result, and Isis::GruenResult::Gain().
Referenced by algorithm().
| double Isis::Gruen::getDefaultGain | ( | ) | const [inline, private] |
| double Isis::Gruen::getDefaultShift | ( | ) | const [inline, private] |
| Gruen::GSLVector Isis::Gruen::getThreshHold | ( | const Chip & | chip | ) | const [private] |
Compute the Affine convergence parameters.
This method should be invoked using either the subsearch or pattern chip since they are both the same size. The six Affine convergence parameters are computed from the size of the chip and the AffineThreshHold1 and AffineThreshHold2 registration parameters.
AffineThreshHold1 governs the shift in line and sample and is used directly as specified in the registration config file.
AffineThreshHold2 governs scaling of sample and line as a function of the number of lines and samples in the chip provided. The value from the registration config file is divided by half the samples for the X Affine component; the Y Affine component is divided by half the number of lines in the chip.
| chip | Chip to use to compute affine convergence threshholds |
Definition at line 718 of file Gruen.cpp.
References _scaleTol, _shearTol, _transTol, Isis::Chip::Lines(), and Isis::Chip::Samples().
Referenced by AdaptiveRegistration().
| double Isis::AutoReg::GoodnessOfFit | ( | ) | const [inline, inherited] |
Return the goodness of fit of the match algorithm.
Definition at line 175 of file AutoReg.h.
References Isis::AutoReg::p_goodnessOfFit.
Referenced by Qisis::ControlPointEdit::registerPoint().
| bool Isis::Gruen::HasConverged | ( | const GSLVector & | alpha, | |
| const GSLVector & | thresh, | |||
| const GruenResult & | results | |||
| ) | const [private] |
Tests Affine parameters for convergence.
This method is invoked after the first iteration to test for convergence of the affine transform components of the Gruen registration algorithm. When the absolute value of all the affine components are less than or equal to its coinciding limit, convergence has been reached.
This method does not consider the radiometric shift and gain parameters in its determination of convergence.
| alpha | Affine transform change from last iteration to test | |
| thresh | Six element array of affine threshholds to test against | |
| results | Results container should any information be needed from it |
Definition at line 747 of file Gruen.cpp.
Referenced by AdaptiveRegistration().
| virtual double Isis::Gruen::IdealFit | ( | ) | const [inline, protected, virtual] |
| void Isis::Gruen::init | ( | Pvl & | pvl | ) | [private] |
Initialize the object.
This method reads from the Algorithm group (if it exists) to set variables used in this object. If not all the keywords are present, then appropriate values are provided.
| PvlObject | &pvl PVL object/groups that contain algorithm parameters |
Definition at line 623 of file Gruen.cpp.
References _affineTol, _defGain, _defShift, _errors, _fitChipScale, _maxIters, _nIters, _prof, _rgainMaxTol, _rgainMinTol, _rshiftTol, _scaleTol, _shearTol, _spiceTol, _totalIterations, _transTol, _unclassified, ConfKey(), initErrorList(), Isis::DbProfile::Name(), pvl(), reset(), Isis::DbProfile::setName(), SetRadiometrics(), and Isis::PvlObject::Traverse.
Referenced by Gruen().
| Gruen::ErrorList Isis::Gruen::initErrorList | ( | ) | const [private] |
Creates an error list from know Gruen errors.
This method creates the list of known/expected Gruen errors that might occur during processing. This should be closely maintained with the GruenErrors enum list.
Definition at line 578 of file Gruen.cpp.
References Isis::CollectorMap< K, T, ComparePolicy, RemovalPolicy, CopyPolicy >::add().
Referenced by init().
| virtual bool Isis::Gruen::IsAdaptive | ( | ) | [inline, virtual] |
Gruen default mode is adaptive.
Reimplemented from Isis::AutoReg.
Reimplemented in Isis::AdaptiveGruen.
Definition at line 103 of file Gruen.h.
Referenced by AlgorithmStatistics().
| bool Isis::Gruen::IsGood | ( | const GruenResult & | result | ) | const [inline] |
Returns the status of the given Gruen result container.
Definition at line 125 of file Gruen.h.
References Isis::GruenResult::IsGood().
| bool Isis::Gruen::IsGood | ( | ) | const [inline] |
Returns status of the last registration result.
Definition at line 123 of file Gruen.h.
References _result.
Referenced by MatchAlgorithm().
| void Isis::Gruen::logError | ( | int | gerrno, | |
| const std::string & | gerrmsg | |||
| ) | [private] |
Logs a Gruen error.
A running count of errors that occur is maintained through this method. If an error occurs that is not in the list, it will also be counted. This would indicate that a new error condition has occured and needs to be added to the list.
| gerrno | One of the errors as defined by GruenError enum | |
| gerrmsg | Optional message although it is ignored in this context |
Definition at line 604 of file Gruen.cpp.
References _errors, _unclassified, Isis::CollectorMap< K, T, ComparePolicy, RemovalPolicy, CopyPolicy >::exists(), and Isis::CollectorMap< K, T, ComparePolicy, RemovalPolicy, CopyPolicy >::get().
Referenced by AdaptiveRegistration(), algorithm(), CheckAffineTolerance(), solve(), and TestConstraints().
Minimization of data set using Gruen algorithm.
This is a very minimal application of the Gruen algorithm that provides the ability to use it in a non-adaptive capacity. This method processes two chips of the same size, pattern and subsearch. The subsearch has typically been extracted in the same manner as the MinimumDifference or MaximumCorrelation routines are utilized.
It simply applies the algorithm to the current state of the two chips, computes the error analysis on it and returns the eigen vector solution as an indication of chip registration integrity.
Note that in this mode, most all the parameters found in the definition file that apply to the adaptive mode are ignored when utilizing the algorithm in this fashion.
| pattern | [in] A Chip object usually containing an nxm area of a cube. Must be the same diminsions as subsearch. | |
| subsearch | [in] A Chip object usually containing an nxm area of a cube. Must be the same diminsions as pattern. This is normally a subarea of a larger portion of the image. |
Implements Isis::AutoReg.
Definition at line 299 of file Gruen.cpp.
References _result, algorithm(), Isis::GruenResult::Eigen(), IsGood(), Isis::Null, reset(), and Isis::GruenResult::update().
Computes the number of minimum valid points.
This method uses the pattern valid percent as specified in the registration config file (or the programmer) to compute the minimum number of valid points from the total.
| totalPoints | Assumed to be total number of relavent pixels in a chip |
Definition at line 769 of file Gruen.cpp.
References Isis::AutoReg::PatternValidPercent().
Referenced by algorithm(), and ValidPoints().
| bool Isis::AutoReg::ModelSurface | ( | std::vector< double > & | x, | |
| std::vector< double > & | y, | |||
| std::vector< double > & | z | |||
| ) | [protected, inherited] |
We will model a 2-d surface as:.
z = a + b*x + c*y + d*x**2 + e*x*y + f*y**2
Then the partial derivatives are two lines:
dz/dx = b + 2dx + ey dz/dy = c + ex + 2fy
We will have a local min/max where dz/dx and dz/dy = 0. Solve using that condition using linear algebra yields:
xlocal = (ce - 2bf) / (4df - ee) ylocal = (be - 2cd) / (4df - ee)
These will be stored in p_chipSample and p_chipLine respectively.
| x | vector of x (sample) values | |
| y | vector of y (line) values | |
| z | vector of z (goodness-of-fit) values |
Definition at line 745 of file AutoReg.cpp.
References a, Isis::LeastSquares::AddKnown(), b, c, Isis::BasisFunction::Coefficient(), d, delta, Isis::Matrix::Determinant(), e, Isis::LeastSquares::Evaluate(), Isis::AutoReg::p_chipLine, Isis::AutoReg::p_chipSample, Isis::AutoReg::p_goodnessOfFit, Isis::AutoReg::p_status, Isis::AutoReg::p_surfaceModelEccentricity, Isis::AutoReg::p_SurfaceModelEccentricityRatioNotMet, Isis::AutoReg::p_surfaceModelEccentricityTolerance, Isis::AutoReg::p_SurfaceModelSolutionInvalid, Isis::LeastSquares::Solve(), Isis::AutoReg::SurfaceModelEccentricityRatioNotMet, and Isis::AutoReg::SurfaceModelSolutionInvalid.
Referenced by Isis::AutoReg::Register().
| PvlKeyword Isis::Gruen::ParameterKey | ( | const std::string & | keyname, | |
| const T & | value, | |||
| const std::string & | unit = "" | |||
| ) | const [inline, private] |
Keyword formatter for Gruen parameters.
Constructs a keyword with actual user/programmer values if provided, otherwise sets the value to "Unbounded".
| T | Type of value to record | |
| keyname | Name of keyword to create | |
| value | Value to set keyword to if in profile | |
| unit | Optional unit value |
Definition at line 253 of file Gruen.h.
References _prof, Isis::DbProfile::exists(), and ValidateKey().
Referenced by ParameterLog().
| PvlGroup Isis::Gruen::ParameterLog | ( | ) | const [private] |
Create a PvlGroup with the Gruen specific parameters.
This method generates a PvlGroup of Gruen algorithm parameters. This routine is called from the AutoReg algorithm specific statistics routine and augments the AutoReg log output.
Definition at line 545 of file Gruen.cpp.
References _affineTol, _defGain, _defShift, _fitChipScale, _maxIters, _rgainMaxTol, _rgainMinTol, _rshiftTol, _scaleTol, _shearTol, _spiceTol, _transTol, ParameterKey(), and ValidateKey().
Referenced by AlgorithmStatistics().
| void Isis::AutoReg::Parse | ( | Pvl & | pvl | ) | [protected, inherited] |
Initialize parameters in the AutoReg class using a PVL specification.
An example of the PVL required for this is:
Object = AutoRegistration
Group = Algorithm
Name = MaximumCorrelation
Tolerance = 0.7
EndGroup
Group = PatternChip
Samples = 21
Lines = 21
EndGroup
Group = SearchChip
Samples = 51
Lines = 51
EndGroup
EndObject
There are many other options that can be set via the pvl and are described in other documentation (see below).
| pvl | The pvl object containing the specification |
Definition at line 136 of file AutoReg.cpp.
References _FILEINFO_, e, Isis::PvlContainer::Filename(), Isis::PvlObject::FindGroup(), Isis::PvlObject::HasGroup(), Isis::PvlContainer::HasKeyword(), maximum, Isis::iException::Message(), minimum, Isis::AutoReg::PatternChip(), pvl(), Isis::AutoReg::SearchChip(), Isis::AutoReg::SetPatternValidPercent(), Isis::AutoReg::SetPatternZScoreMinimum(), Isis::AutoReg::SetReductionFactor(), Isis::Chip::SetSize(), Isis::AutoReg::SetSubPixelAccuracy(), Isis::AutoReg::SetSurfaceModelDistanceTolerance(), Isis::AutoReg::SetSurfaceModelEccentricityRatio(), Isis::AutoReg::SetSurfaceModelWindowSize(), Isis::AutoReg::SetTolerance(), Isis::Chip::SetValidRange(), Isis::PvlObject::Traverse, Isis::ValidMaximum, and Isis::ValidMinimum.
Referenced by Isis::AutoReg::AutoReg().
| Chip* Isis::AutoReg::PatternChip | ( | ) | [inline, inherited] |
Return pointer to pattern chip.
Definition at line 140 of file AutoReg.h.
References Isis::AutoReg::p_patternChip.
Referenced by Isis::AutoReg::Parse(), Qisis::ControlPointEdit::registerPoint(), and Qisis::ControlPointEdit::saveChips().
| double Isis::AutoReg::PatternValidPercent | ( | ) | const [inline, inherited] |
Return pattern valid percent.
Definition at line 167 of file AutoReg.h.
References Isis::AutoReg::p_patternValidPercent.
Referenced by MinValidPoints().
This method reduces the given chip by the given reduction factor.
Used to speed up the match algorithm.
| reductionFactor |
Definition at line 348 of file AutoReg.cpp.
References Isis::Statistics::AddData(), Isis::Statistics::Average(), Isis::Chip::GetValue(), line, Isis::Chip::Lines(), Isis::Null, Isis::Statistics::Reset(), sample, Isis::Chip::Samples(), Isis::Chip::SetValue(), and stats.
Referenced by Isis::AutoReg::Register().
| Chip* Isis::AutoReg::ReducedFitChip | ( | ) | [inline, inherited] |
Return pointer to reduced fix chip.
Definition at line 155 of file AutoReg.h.
References Isis::AutoReg::p_reducedFitChip.
| Chip* Isis::AutoReg::ReducedPatternChip | ( | ) | [inline, inherited] |
Return pointer to reduced pattern chip.
Definition at line 149 of file AutoReg.h.
References Isis::AutoReg::p_reducedPatternChip.
| Chip* Isis::AutoReg::ReducedSearchChip | ( | ) | [inline, inherited] |
Return pointer to reduced search chip.
Definition at line 152 of file AutoReg.h.
References Isis::AutoReg::p_reducedSearchChip.
| AutoReg::RegisterStatus Isis::AutoReg::Register | ( | ) | [inherited] |
Walk the pattern chip through the search chip to find the best registration.
Definition at line 392 of file AutoReg.cpp.
References _FILEINFO_, Isis::AutoReg::AdaptiveRegistration(), Isis::AutoReg::CompareFits(), Isis::AutoReg::ComputeChipZScore(), Isis::Chip::CubeLine(), Isis::Chip::CubeSample(), Isis::AutoReg::FitChipNoData, Isis::AutoReg::FitChipToleranceNotMet, Isis::Chip::GetValue(), Isis::AutoReg::Init(), Isis::AutoReg::IsAdaptive(), Isis::AutoReg::IsIdeal(), Isis::Chip::IsValid(), line, Isis::Chip::Lines(), Isis::AutoReg::Match(), Isis::iException::Message(), Isis::AutoReg::ModelSurface(), Isis::Null, Isis::AutoReg::p_bestFit, Isis::AutoReg::p_bestLine, Isis::AutoReg::p_bestSamp, Isis::AutoReg::p_chipLine, Isis::AutoReg::p_chipSample, Isis::AutoReg::p_cubeLine, Isis::AutoReg::p_cubeSample, Isis::AutoReg::p_distanceTolerance, Isis::AutoReg::p_fitChip, Isis::AutoReg::p_FitChipNoData, Isis::AutoReg::p_FitChipToleranceNotMet, Isis::AutoReg::p_goodnessOfFit, Isis::AutoReg::p_patternChip, Isis::AutoReg::p_PatternChipNotEnoughValidData, Isis::AutoReg::p_patternValidPercent, Isis::AutoReg::p_PatternZScoreNotMet, Isis::AutoReg::p_reducedFitChip, Isis::AutoReg::p_reducedPatternChip, Isis::AutoReg::p_reducedSearchChip, Isis::AutoReg::p_reduceFactor, Isis::AutoReg::p_searchChip, Isis::AutoReg::p_status, Isis::AutoReg::p_subpixelAccuracy, Isis::AutoReg::p_Success, Isis::AutoReg::p_SurfaceModelDistanceInvalid, Isis::AutoReg::p_SurfaceModelNotEnoughValidData, Isis::AutoReg::p_Total, Isis::AutoReg::p_windowSize, Isis::AutoReg::PatternChipNotEnoughValidData, Isis::AutoReg::PatternZScoreNotMet, Isis::AutoReg::Reduce(), Isis::Chip::Samples(), Isis::Chip::SetChipPosition(), Isis::Chip::SetSize(), Isis::Chip::SetValue(), sl, ss, Isis::AutoReg::Success, Isis::AutoReg::SurfaceModelDistanceInvalid, Isis::AutoReg::SurfaceModelNotEnoughValidData, Isis::Chip::TackLine(), Isis::Chip::TackSample(), and Isis::AutoReg::Tolerance().
Referenced by Qisis::ControlPointEdit::registerPoint().
| Pvl Isis::AutoReg::RegistrationStatistics | ( | ) | [inherited] |
This returns the cumulative registration statistics.
That is, the Register() method accumulates statistics regard the errors each time is called. Invoking this method returns a PVL summary of those statisitics
Definition at line 920 of file AutoReg.cpp.
References Isis::AutoReg::AlgorithmStatistics(), Isis::AutoReg::p_FitChipNoData, Isis::AutoReg::p_FitChipToleranceNotMet, Isis::AutoReg::p_PatternChipNotEnoughValidData, Isis::AutoReg::p_PatternZScoreNotMet, Isis::AutoReg::p_Success, Isis::AutoReg::p_SurfaceModelDistanceInvalid, Isis::AutoReg::p_SurfaceModelEccentricityRatioNotMet, Isis::AutoReg::p_SurfaceModelNotEnoughValidData, Isis::AutoReg::p_SurfaceModelSolutionInvalid, Isis::AutoReg::p_Total, pvl(), and stats.
| PvlGroup Isis::AutoReg::RegTemplate | ( | ) | [inherited] |
This function returns the keywords that this object was created from.
Definition at line 1002 of file AutoReg.cpp.
References Isis::PvlObject::FindGroup(), Isis::PvlObject::HasGroup(), Isis::PvlContainer::HasKeyword(), Isis::AutoReg::p_template, Isis::AutoReg::SetPatternValidPercent(), and Isis::PvlObject::Traverse.
| void Isis::Gruen::reset | ( | ) | [private] |
Reset registration-dependant counters only.
This method is intended to be invoked to reset interal variables that track or govern behavior pertaining to the registration of two chips. It should be invoked as the first call prior to calling the algorithm method for a new registration.
Definition at line 673 of file Gruen.cpp.
References _nIters, _result, getDefaultGain(), getDefaultShift(), Isis::GruenResult::setGain(), and Isis::GruenResult::setShift().
Referenced by AdaptiveRegistration(), init(), and MatchAlgorithm().
| void Isis::Gruen::resetStats | ( | ) | [private] |
Reset Gruen statistics as needed.
Definition at line 685 of file Gruen.cpp.
References _eigenStat, _gainStat, _iterStat, _shiftStat, and Isis::Statistics::Reset().
| const GruenResult& Isis::Gruen::Results | ( | ) | const [inline] |
| Chip* Isis::AutoReg::SearchChip | ( | ) | [inline, inherited] |
Return pointer to search chip.
Definition at line 143 of file AutoReg.h.
References Isis::AutoReg::p_searchChip.
Referenced by Isis::AutoReg::Parse(), Qisis::ControlPointEdit::registerPoint(), and Qisis::ControlPointEdit::saveChips().
| void Isis::AutoReg::SetChipLine | ( | double | line | ) | [inline, protected, inherited] |
Sets the search chip subpixel line that matches the pattern tack line.
| line |
Definition at line 237 of file AutoReg.h.
References Isis::AutoReg::p_chipLine.
Referenced by AdaptiveRegistration().
| void Isis::AutoReg::SetChipSample | ( | double | sample | ) | [inline, protected, inherited] |
Sets the search chip subpixel sample that matches the pattern tack sample.
| sample |
Definition at line 228 of file AutoReg.h.
References Isis::AutoReg::p_chipSample.
Referenced by AdaptiveRegistration().
| void Isis::AutoReg::SetGoodnessOfFit | ( | double | fit | ) | [inline, protected, inherited] |
Sets the goodness of fit for adaptive algorithms.
| Fit | Fit value to set |
Definition at line 244 of file AutoReg.h.
References Isis::AutoReg::p_bestFit.
Referenced by AdaptiveRegistration().
| void Isis::AutoReg::SetPatternValidPercent | ( | const double | percent | ) | [inherited] |
Set the amount of data in the pattern chip that must be valid.
For example, a 21x21 pattern chip has 441 pixels. If percent is 75 then at least 330 pixels pairs must be valid in order for a comparision between the pattern and search sub-region to occur. That is, both the pattern pixel and search pixel must be valid to be counted. Pixels are considered valid based on the min/max range specified on each of the Chips (see Chip::SetValidRange method).
If the pattern chip reduction option is used this percentage will apply to all reduced patterns. Additionally, the pattern sampling effects the pixel count. For example if pattern sampling is 50% then only 220 pixels in the 21x21 pattern are considered so 165 must be valid.
| percent | Percentage of valid data between 0 and 100, default is 50% if never invoked |
Definition at line 234 of file AutoReg.cpp.
References _FILEINFO_, Isis::iException::Message(), and Isis::AutoReg::p_patternValidPercent.
Referenced by Isis::AutoReg::AutoReg(), Isis::AutoReg::Parse(), and Isis::AutoReg::RegTemplate().
| void Isis::AutoReg::SetPatternZScoreMinimum | ( | double | minimum | ) | [inherited] |
Set the minimum pattern zscore.
This option is used to ignore pattern chips which are bland (low standard deviation). If the minimum or maximum pixel value in the pattern chip does not meet the minimum zscore value (see a statisitcs book for definition of zscore) then invalid registration will occur.
| minimum | The minimum zscore value for the pattern chip. Default is 1.0 |
Definition at line 255 of file AutoReg.cpp.
References _FILEINFO_, Isis::iException::Message(), and Isis::AutoReg::p_minimumPatternZScore.
Referenced by Isis::AutoReg::AutoReg(), and Isis::AutoReg::Parse().
| void Isis::Gruen::SetRadiometrics | ( | const double & | gain = 0.0, |
|
| const double & | shift = 0.0 | |||
| ) |
Sets established radiometric parameters for registration processes.
This method provides a mechanism for establishing predetermined values for registration activities. This is intended to be used for the DEM generation processing where points are grown around seed points. This is intended to lead to rapid convergence of points surrounding established seed points.
This should be used in conjuction with the resulting Affine transform as determined from the seed point.
Note that once this is established, it remains constant for all subsequent registration processes. To reset the default, all this method with no arguments.
Also note that these defaults can be established in the input AutoReg definition file.
These values are set when reset() is called - typically at the start of any adaptive application of the Gruen algorithm.
| gain | Precomputed radiometric gain value to use as default | |
| shift | Precomputed radiometric shift value to use as default |
Definition at line 70 of file Gruen.cpp.
References _defGain, and _defShift.
Referenced by init().
| void Isis::AutoReg::SetReductionFactor | ( | int | factor | ) | [inherited] |
Set the reduction factor used to speed up the pattern matching algorithm.
| factor |
Definition at line 331 of file AutoReg.cpp.
References _FILEINFO_, Isis::iException::Message(), and Isis::AutoReg::p_reduceFactor.
Referenced by Isis::AutoReg::AutoReg(), and Isis::AutoReg::Parse().
| void Isis::AutoReg::SetSubPixelAccuracy | ( | bool | on | ) | [inherited] |
If the sub-accuracy is enable the Register() method will attempt to match the pattern chip to the search chip at sub-pixel accuracy, otherwise it will be registered at whole pixel accuracy.
| on | Set the state of registration accuracy. The default is sub-pixel accuracy is on |
Definition at line 212 of file AutoReg.cpp.
References Isis::AutoReg::p_subpixelAccuracy.
Referenced by Isis::AutoReg::AutoReg(), and Isis::AutoReg::Parse().
| void Isis::AutoReg::SetSurfaceModelDistanceTolerance | ( | double | distance | ) | [inherited] |
Set a distance the surface model solution is allow to move away from the best whole pixel fit in the fit chip.
| distance | The distance allowed to move in pixels. Must be greater than zero. |
Definition at line 316 of file AutoReg.cpp.
References _FILEINFO_, Isis::iException::Message(), and Isis::AutoReg::p_distanceTolerance.
Referenced by Isis::AutoReg::AutoReg(), and Isis::AutoReg::Parse().
| void Isis::AutoReg::SetSurfaceModelEccentricityRatio | ( | double | eccentricityRatio | ) | [inherited] |
A 1:1 ratio represents a perfect circle.
Allowing the user to set this ratio lets them determine which points to throw out if the surface model gets too elliptical.
| eccentricityRatio |
Definition at line 300 of file AutoReg.cpp.
References _FILEINFO_, Isis::iException::Message(), and Isis::AutoReg::p_surfaceModelEccentricityTolerance.
Referenced by Isis::AutoReg::AutoReg(), and Isis::AutoReg::Parse().
| void Isis::AutoReg::SetSurfaceModelWindowSize | ( | int | size | ) | [inherited] |
Set the surface model window size.
The pixels in this window will be used to fit a surface model in order to compute sub-pixel accuracy. In some cases the default (3x3) and produces erroneous sub-pixel accuracy values.
| size | The size of the window must be three or greater and odd. |
Definition at line 284 of file AutoReg.cpp.
References _FILEINFO_, Isis::iException::Message(), and Isis::AutoReg::p_windowSize.
Referenced by Isis::AutoReg::AutoReg(), and Isis::AutoReg::Parse().
| void Isis::AutoReg::SetTolerance | ( | double | tolerance | ) | [inherited] |
Set the tolerance for an acceptable goodness of fit.
| tolerance | This tolerance is used to test against the goodness of fit returned by the MatchAlgorith method after a surface model has been fit. See TestGoodnessOfFit |
Definition at line 271 of file AutoReg.cpp.
References Isis::AutoReg::p_tolerance.
Referenced by Isis::AutoReg::AutoReg(), and Isis::AutoReg::Parse().
| double Isis::Gruen::Shift | ( | ) | const [inline] |
Returns the radiometric shift value from the last solution.
Definition at line 108 of file Gruen.h.
References _result, and Isis::GruenResult::Shift().
Referenced by algorithm().
| bool Isis::Gruen::solve | ( | GruenResult & | result | ) | [protected] |
Computes solution and error analysis using Cholesky/Jacobi methods.
This method computes the affine and radiometric parameter solution and associated errors/uncertainty from the algorithm() processing.
The affine parameters are solved using Cholesky decomposition. Error analysis is computed using Jacobian eigenvector methods. The GNU Scientific Library (GSL) is used to apply these routines.
See http://www.gnu.org/software/gsl/ for additional details on the GNU Scientific Library.
| result | Input parameters provided to compute solution. This container is also updated by this method with the solution and error analysis. |
Definition at line 203 of file Gruen.cpp.
References Isis::GruenResult::alpha, Isis::GruenResult::ata, Isis::GruenResult::atl, c, Isis::GSL::GSLUtility::check(), Isis::iException::Clear(), Isis::GSL::GSLUtility::Columns(), Isis::GruenResult::eigen, Isis::iException::Errors(), Isis::GSL::GSLUtility::free(), Isis::GruenResult::gerrmsg, Isis::GruenResult::gerrno, Isis::GSL::GSLUtility::getInstance(), Isis::GSL::GSLUtility::GSLTogsl(), Isis::GSL::GSLUtility::identity(), Isis::GruenResult::isGood, Isis::GruenResult::kmat, logError(), Isis::GSL::GSLUtility::Rows(), Isis::GruenResult::skmat, Isis::GruenResult::Variance(), and x.
Referenced by algorithm().
| double Isis::Gruen::SpiceTolerance | ( | ) | const [inline] |
| PvlGroup Isis::Gruen::StatsLog | ( | ) | const [private] |
Create a PvlGroup with the Gruen specific statistics.
This method generates a PvlGroup from statistics collected for a particular Gruen algorithm application. This routine is called from the AutoReg algorithm specific statistics routine and augments the AutoReg statistics log output.
Definition at line 508 of file Gruen.cpp.
References _eigenStat, _gainStat, _iterStat, _shiftStat, _totalIterations, Isis::Statistics::Average(), Isis::Statistics::Maximum(), Isis::Statistics::Minimum(), Isis::Statistics::StandardDeviation(), stats, and ValidateKey().
Referenced by AlgorithmStatistics().
| AutoReg::RegisterStatus Isis::Gruen::Status | ( | ) | const [inline, private] |
Returns status of the last Gruen registration result.
Definition at line 311 of file Gruen.h.
References _result.
Referenced by AdaptiveRegistration().
| AutoReg::RegisterStatus Isis::Gruen::Status | ( | const GruenResult & | result | ) | const [private] |
Returns the proper status given a Gruen result container.
This method will return registration status consistant with AutoReg::RegisterStatus return codes.
| result | Gruen result container used to determine status |
Definition at line 971 of file Gruen.cpp.
References Isis::AutoReg::AdaptiveAlgorithmFailed, Isis::GruenResult::IsGood(), and Isis::AutoReg::Success.
| bool Isis::Gruen::TestConstraints | ( | const bool & | done, | |
| GruenResult & | result | |||
| ) | [private] |
Test user limits/contraints after the algorithm has converged.
This method is invoked immediately after the Gruen algorithm has converged to test against user specified limits. This call is only valid in the adaptive context as much of the error checking is handled by AutoReg when using the non-adaptive algorithm.
This method tests for convergence, maximum iterations exceeded, tolerance limits of radiometric shift and gain and whether the eigenvalue of the solution exceeds the limit.
The result container is altered should a constraint not be meet which indicates the registration failed.
| done | Input parameter that indicates convergence has occurred | |
| result | Container with results update by status of contraint check |
Definition at line 830 of file Gruen.cpp.
References _eigenStat, _gainStat, _iterStat, _maxIters, _rgainMaxTol, _rgainMinTol, _rshiftTol, _shiftStat, Isis::Statistics::AddData(), Isis::GruenResult::Eigen(), Isis::GruenResult::Gain(), Isis::GruenResult::gerrmsg, Isis::GruenResult::gerrno, Isis::GruenResult::IsGood(), Isis::GruenResult::isGood, Isis::GruenResult::Iterations(), logError(), Isis::GruenResult::Shift(), and Isis::AutoReg::Tolerance().
Referenced by AdaptiveRegistration().
| double Isis::AutoReg::Tolerance | ( | ) | const [inline, inherited] |
Return match algorithm tolerance.
Definition at line 170 of file AutoReg.h.
References Isis::AutoReg::p_tolerance.
Referenced by Isis::AutoReg::Register(), and TestConstraints().
| Affine Isis::Gruen::UpdateAffine | ( | GruenResult & | result, | |
| const Affine & | gtrans | |||
| ) | [private] |
Updates the affine transform with the final iterative solution.
This method is called at the end of each iteration that updates the affine transform with the sum of all prior affine changes. The affine for the current result is added to the cummulative result container and the incremental affine is added to the cummulate transform.
| result | Container representing the last iteration solution | |
| gtrans | Accumulating affine transform for search chip |
Definition at line 897 of file Gruen.cpp.
References _result, a, Isis::GruenResult::Alpha(), Isis::Affine::Forward(), and Isis::GruenResult::update().
Referenced by AdaptiveRegistration().
Updates the (search) chip with the final Affine transform.
This method applies the convergent Affine transform parameters to the chip provided. The accummulated transform only represents the result of the Gruen algorithm. Therefore, any existing Affine transform used to load the orginal chip will be added to it for the final resulting solution.
When completed, in theory, the chip can be used to reload from the file and it should match well with the original pattern chip on the final iteration of the Gruen algorithm which converged.
| chip | Chip to update with accummulated Affine transform | |
| affine | Gruen accummulated Affine transform to add to chip |
Definition at line 924 of file Gruen.cpp.
References c, Isis::Affine::Forward(), Isis::Affine::getIdentity(), Isis::Chip::getTransform(), and Isis::Chip::setTransform().
Referenced by AdaptiveRegistration().
| PvlKeyword Isis::Gruen::ValidateKey | ( | const std::string | keyname, | |
| const double & | value, | |||
| const std::string & | unit = "" | |||
| ) | const [inline, private] |
Checks value of key, produces appropriate value.
This function checks the value of the keyword for specialness and will create the appropriate keyword if it is special.
| keyname | Name of keyword to create | |
| value | Keyword value | |
| unit | Optional unit qualifer with value |
Definition at line 275 of file Gruen.h.
References Isis::IsSpecial().
Referenced by ParameterKey(), ParameterLog(), and StatsLog().
Determines if number of points is valid percentage of all points.
Computes the number of minimum valid points from user specified percentage and tests the acutal number used.
| totalPoints | Total number of possible valid points in chip | |
| nPoints | Actual number of valid points used in chips |
Definition at line 786 of file Gruen.cpp.
References MinValidPoints().
Referenced by algorithm().
| void Isis::AutoReg::ZScores | ( | double & | score1, | |
| double & | score2 | |||
| ) | const [inline, inherited] |
Return the ZScores of the pattern chip.
| score1 | First Z Score | |
| score2 | Second Z Score |
Definition at line 197 of file AutoReg.h.
References Isis::AutoReg::p_ZScore1, and Isis::AutoReg::p_ZScore2.
GruenResult Isis::Gruen::_result [private] |
last result, cummulative
Definition at line 197 of file Gruen.h.
Referenced by AdaptiveRegistration(), CheckAffineTolerance(), ErrorAnalysis(), Gain(), IsGood(), MatchAlgorithm(), reset(), Results(), Shift(), Status(), and UpdateAffine().
PvlObject Isis::AutoReg::p_template [protected, inherited] |
AutoRegistration object that created this projection.
Definition at line 284 of file AutoReg.h.
Referenced by Isis::AutoReg::AutoReg(), and Isis::AutoReg::RegTemplate().