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cnetwinnow

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Sets problem measures to ignored based on an examination of the residual histogram.

Description
Categories
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History


Description

After jigsaw has done a bundle adjustment on a group of overlapping Isis, level 1, cubes every image measure in the network will have associated residuals. A historgram of the residuals is constructed in order to determine the magnitude at which the noise (bad data) starts to dominate the solution. The points are segregated into three categories in assending order of residual magnitude: inocent, suspect, and guilty. The progam then attempts to ingore all the suspect and guilty measures based on the criteria for measure rejection provided. If guilty measures cannot be ingored a report is generated documenting why. No additional action is taken if suspect measure cannot be elliminated.

Known Issues

Not spliting a network into islands is one of the primary considerations for whether or not a measure can be ingorned. However, having even a single measure conecting mass of images A to mass of image B is currently considered sufficient for 'connecting' them together as a network. Obviously this is a necissary, though grossly insufficient requirment.

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Parameter Groups

Files

Name Description
FROMLIST cube list
CNET Input control network
ONET Output control network
FILE_PREFIXoutput file prefix

Histogram Analysis Parameters--The user is advised to use caution if changing the defualts

Name Description
BIN_WIDTHThe width of the histogram bins in unweighted pixels.
SUSPECT_BUMP_PERCENT The percent that that a local histogram maximum must be greater than a local minimum to be considered suspect.
GUILTY_BUMP_PERCENT The percent that that a local histogram maximum must be greater than a local minimum to be considered guilty.
SUSPECT_FLOORThere will be no attempt to set residuals smaller than this user defined limit to ignored.
GUILTY_FLOOREvery residual greater than user defined GUILTY_FLOOR is guilty

Measure Rejection Criteria

Name Description
HULL_REDUCTION_PERCENTMaximum precent reduction to the area of the convex hull of the measures in an image.
MEASURE_REDUCTION_PERCENTMaximum precent reduction of the measures in an image.

Files: FROMLIST

Description

This file contains a list of all cubes in the control network

Type filename
File Mode input
Filter *.txt *.lis

Files: CNET

Description

This file is a control network generated from programs such as autoseed or qnet. It contains the control points and associated measures.

Type filename
File Mode input
Filter *.net

Files: ONET

Description

This output file contains the updated control network with the problem measures set to ignor.

Type filename
File Mode output
Filter *.net

Files: FILE_PREFIX

Description

2 Reports will be generated: 1. FILE_PREFIXGuilty.csv, a report of apparently bad points that could not be set to ignored, 2. FILE_PREFIXIgnored.csv, a report of all the measures that were set to ignor.

Type string
Internal Default none

Histogram Analysis Parameters--The user is advised to use caution if changing the defualts: BIN_WIDTH

Description

The program will build and analyze a histogram of the R^2 residual lengths. This prameter tells the software how wide to make each bin. Unless the user has studied the behaviour of residuals (particularly with regard to their networks), we do not advise changing the default.

Type double
Default 0.1
Minimum 0 (exclusive)

Histogram Analysis Parameters--The user is advised to use caution if changing the defualts: SUSPECT_BUMP_PERCENT

Description

If all of the measurements in network belong to Gaussian distribution (one of the typical assumptions in least squares analysis) then the residual histogram should be strictly decreasing in the tail. There should be only one local maxima near the median (a results of using equal distance bins instead of equal area). All other local maxima are 'bumps' and reveal where the assumption of Gaussian noise is breaking down. The SUSPECT_BUMP_PERCENT is the minimum bump height (in percentage of the preceding local minima) for a bump to be considered suspect. And barring user override will be the boundary between inocent and suspect points. Changing the default is not typically recomended.

Type double
Default 5
Minimum 0 (inclusive)
Maximum 100 (inclusive)

Histogram Analysis Parameters--The user is advised to use caution if changing the defualts: GUILTY_BUMP_PERCENT

Description

If all of the measurements in network belong to Gaussian distribution (one of the typical assumptions in least squares analysis) then the residual histogram should be strictly decreasing in the tail. There should be only one local maxima near the median (a results of using equal distance bins instead of equal area). All other local maxima are 'bumps' and reveal where the assumption of Gaussian noise is breaking down. The GUILTY_BUMP_PERCENT is the minimum bump height (in percentage of the preceding local minima) for a bump to be considered guilty. And barring user override will be the boundary between suspect and guilty points. Changing the default is not typically recomended.

Type double
Default 10
Minimum 0 (inclusive)
Maximum 100 (inclusive)

Histogram Analysis Parameters--The user is advised to use caution if changing the defualts: SUSPECT_FLOOR

Description

SUSPECT_FLOOR is the lowest that the boundary between inocent and suspect residual magnitudes will slip. Histogram analysis may however result in a higher magnitude boundary.

Type double
Default 1.0
Minimum 0.0 (inclusive)

Histogram Analysis Parameters--The user is advised to use caution if changing the defualts: GUILTY_FLOOR

Description

GUILTY_FLOOR is the highest that the boundary between suspect and guilty residual magnitudes will slip. Histogram analysis may however result in a lower magnitude boundary--strickly greater than the inocent-suspect boundary.

Type double
Default 2.5
Minimum 0.0 (inclusive)

Measure Rejection Criteria: HULL_REDUCTION_PERCENT

Description

Maximum precent reduction to the area of the convex hull of the measures in an image.

Type double
Default 15
Minimum 0 (inclusive)
Maximum 100 (inclusive)

Measure Rejection Criteria: MEASURE_REDUCTION_PERCENT

Description

Maximum precent reduction of the measures in an image.

Type double
Default 30
Minimum 0 (inclusive)
Maximum 100 (inclusive)

History

Orrin Thomas2012-04-13 Original version