Package boofcv.alg.disparity.block
package boofcv.alg.disparity.block
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ClassDescriptionInterface for computing disparity scores across an entire rowBlockRowScore.ArrayF32<T extends ImageBase<T>>Computes the block disparity score using a
CensusTransform.BlockStereoMutualInformationimplementation.BlockRowScoreNcc<T extends ImageBase<T>>Score using NCC.Computes the Sum of Absolute Difference (SAD) for block matching based algorithms.DisparitySelect<Array,T extends ImageGray> Selects the best disparity given the set of scores calculated byDisparityBlockMatch.DisparitySparseSelect<ArrayType>Computes the disparity given disparity score calculations provided byDisparitySparseRectifiedScoreBM.SelectDisparityBasicWta<Array,Disparity extends ImageGray> Selects the optimal disparity given a set of scores using a Winner Take All (WTA) strategy without any validation.SelectDisparityWithChecksWta<Array,DI extends ImageGray<DI>> 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.Disparity score functions for sparse Census.Applies a census transform to the input image and creates a new transformed image patch for later processingSparseScoreRectifiedCensus.S32<T extends GrayI<T>>Computes census score for transformed images of type S32SparseScoreRectifiedCensus.S64<T extends GrayI<T>>Computes census score for transformed images of type S64SparseScoreRectifiedCensus.U8<T extends GrayI<T>>Computes census score for transformed images of type U8SparseScoreRectifiedNcc<T extends ImageGray<T>>Compute NCC error for sparse disparity.Computes sparse SAD scores from rectified input images