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<strong>MOPEX</strong> User’s <strong>Guide</strong><br />
This module does Multiframe Temporal Outlier detection (§8.2.2) on the interpolated input<br />
images. The interpolated input frames are stacked, and for each pixe l position in the<br />
interpolated grid, the trimmed mean and standard deviation of the pixel values in the stack is<br />
calculated. The pixel values outside of the user-specified asymmetrical multi-sigma<br />
thresholds are classified as outliers. This method detects both moving objects and radhits. It is<br />
not meant to be used in the cases of shallow coverage.<br />
The thresholds - Bottom Threshold and Top Threshold - can be set to 0, which is the default.<br />
In this case, the decision of declaring a particular pixel an outlier is put off until running the<br />
Mosaic RMask module. The advantage of doing it this way is that the user can experiment<br />
with different thresholds for outliers in the Mosaic RMask module, without having to rerun<br />
the Mosaic Outlier module.<br />
5.6.15 Mosaic Modules: Mosaic Box Outlier<br />
Command Line Equivalent: run_mosaic_box_outlier<br />
Default Output Directory: /BoxOutlier-mosaic<br />
De pe nds On: Mosaic Interpolate<br />
Important Notes: Using this module does not mean that <strong>MOPEX</strong> will automatically use the<br />
results for outlier detection. In order to use the results from this module, you must set Use Box<br />
Outlier For Rmask in the Mosaic RMask module and set the RMask Fatal Mask Bit Pattern in<br />
the Initial Setup module to use bit 3. Note that this is not the same as setting it to a value of 3. See<br />
§8.11: Fatal Mask Bit Patterns for more information.<br />
PURPOSE<br />
This module uses the Box Outlier rejection method to flag bad pixels (see §8.2.4). The<br />
method is designed to use both the temporal and spatial information like the Dual Outlier, but<br />
it uses the statistical analysis of the kind used by Multiframe Temporal Outlier. In the<br />
identification of temporal outliers, neighboring pixels are utilized to ensure the correct<br />
classification.<br />
INPUT<br />
Box Size X(Y) direction: (int) The X (Y) size of the box of neighboring pixels used for<br />
outlier detections.<br />
Mosaicking (mosaic.pl) 76<br />
Mosaic Modules