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ISIS 2

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ISIS Application Documentation


fillgap

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Compute interpolations to replace special pixels.

Overview Parameters Example 1 Example 2 Example 3

Description

This program will fill in the gaps of a cube (i.e. replace special pixels with DN values) by using an interpolation scheme and a direction specified by the user.

Note: This application will not extrapolate DN values beyond the endpoints of a data set. For example, if you choose to fill gaps that run across lines, then any special pixel values in the first or last vertical column of the image will not be filled. If any of these are not in a corner, you can run fillgap again using the output of the first run as input and SAMPLE as the DIRECTION parameter. Corner pixels can be filled by using the specpix application or the lowpass filter application.


Categories


History

Stacy Alley2007-08-08 based off slither - first version of fillgap
Christopher Austin2008-01-30 Changed INTERP option CUBIC's name to CUBICCONVOLUTION to correlate with other apps using the INTERP param.
Jeannie Walldren2008-11-05 Removed references to DataInterp class and replaced them with NumericalApproximation class.
Jeannie Walldren2009-04-21 Added an exception catch so the application may continue if the interpolation fails for some pixel. Added a message to the log to inform users how many pixels were not filled. Updated user documentation to explain what they may do if this occurs. Changed the INTERP parameter CUBICCONVOLUTION back to CUBIC since this application uses a cubic spline, not cubic convolution. Added test cases and documentation examples.

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File Modified: 02/21/2025 21:48:35
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Files: FROM


Description

Input file to be filled.

Type cube
File Mode input
Filter *.cub
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Files: TO


Description

Output cube.

Type cube
File Mode output
Filter *.cub
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X

Interpolation Scheme: INTERP


Description

fillgap provides 3 different interpolation options. The interpolation option chosen is used to compute a continuous (or piecewise continous) interpolation so that each line and sample has a transform location that maps the output line and sample to a shifted input line and sample. These interpolations provide this mapping. This is done by collecting the known DN values for each line or sample column and using the chosen interpolation scheme to approximate the missing DN values (special pixels).

Type string
Default CUBIC
Option List:
Option Brief Description
LINEARLinear Interpolation of lines and samples This interpolation type is used to determine intermediate line and sample shifts for each line. Linear interpolation is piecewise discontinuous. This interpolation option requires a minimum 2 points.
CUBICNatural Cubic Spline interpolation of each line or sample column This interpolation uses a cubic spline with natural boundary conditions for interpolation of each line and sample shift. The resulting curve is piecewise cubic on each interval with matching first and second derivatives at the supplied data points. The second derivative is chosen to be zero at the first point and last point. This interpolation option requires a minimum of 3 points.
AKIMAAkima Spline interpolation of each line and sample This interpolation uses a non-rounded Akima spline with natural boundary conditions for interpolation of each line and sample shift. This spline uses the non-rounded corner algorithm of Wodicka. It requires a minimum of 5 points.
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Direction: DIRECTION


Description

This is the direction of the special pixels across the image. If the special pixels run through the bands of the image data, try both directions to see which works best.

Type string
Default SAMPLE
Option List:
Option Brief Description
SampleAcross samples The special pixels run horizontally across the image samples.
LineAcross lines The special pixels run vertically across the image lines.
BandAcross Bands The special pixels run 3-D through the image bands.
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