Package boofcv.alg.feature.disparity

Interface Summary

Interface	Description
DisparitySelect<Array,T extends boofcv.struct.image.ImageGray>	Selects the best disparity given the set of scores calculated by DisparityScoreSadRect.
DisparitySparseSelect<ArrayType>	Computes the disparity given disparity score calculations provided by DisparitySparseScoreSadRect.

Class Summary

Class	Description
DisparityScoreRowFormat<Input extends boofcv.struct.image.ImageGray,Disparity extends boofcv.struct.image.ImageGray>	Base class for all dense stereo disparity score algorithms whose score's can be processed by DisparitySelect.
DisparityScoreSadRect<Input extends boofcv.struct.image.ImageGray,Disparity extends boofcv.struct.image.ImageGray>	Computes the disparity SAD score efficiently for a single rectangular region while minimizing CPU cache misses.
DisparityScoreWindowFive<Input extends boofcv.struct.image.ImageGray,Disparity extends boofcv.struct.image.ImageGray>	Scores the disparity for a point using multiple rectangular regions in an effort to reduce errors at object borders, based off te 5 region algorithm described in [1].
DisparitySparseScoreSadRect<ArrayData,Input extends boofcv.struct.image.ImageGray>	Computes disparity SAD scores using a rectangular region at the specified points only along the x-axis.
SelectRectBasicWta<Array,Disparity extends boofcv.struct.image.ImageGray>	Selects the optimal disparity given a set of scores using a Winner Take All (WTA) strategy without any validation.
SelectRectStandard<Array,T extends boofcv.struct.image.ImageGray>	Selects the disparity with the smallest error, which is known as the winner takes all (WTA) strategy.
SelectSparseStandardWta<ArrayType>	Selects the disparity the smallest error and optionally applies several different types of validation to remove false positives.