Prediction Capabilities of Boolean and Stack Filters for Lossless Image Compression

This paper proposes optimal Boolean, stack, and FIR-Boolean hybrid filters for realizing the prediction stage in lossless grey-level image compression. New optimal design procedures for Boolean filters are introduced, where the optimality criterion is the Error Entropy (EE). The use of the EE-optimal and MAE-optimal Boolean and stack filters in the sequential prediction structure is considered, under different instances: global-optimal, block-optimal, adaptive-size-block-optimal and multiresolution. An extensive simulation study is carried out for analyzing and comparing the performances of the newly introduced predictors and various other sequential predictors. The EE-optimal Boolean predictors prove to be the most efficient predictors. More refined filtering structures, such as block-optimal or adaptive-size-block-optimal are suitable for the prediction task when the prediction mask ought to be small. The proposed progressive transmission structure based on optimal Boolean prediction is shown to outperform HINT [1] progressive lossless coding scheme.