Direction-adaptive hierarchical decomposition for image coding

A new model of decomposing an image hierarchically into direction-adaptive subbands using pixel-wise direction estimation is presented. For each decomposing operation, an input image is divided into two parts: a base image subsampled from the input image and subband components. The subband components consist of residuals of estimating the pixels skipped through the subsampling, which ensures the invertibility of the decomposition. The estimation is performed in a direction-adaptive way, whose optimal direction is determined by a L1 norm criterion for each pixel, aiming to achieve good energy compaction that is suitable for image coding. Furthermore, since the L1 norms are obtained from the base image alone, we do not need to retain the directional information explicitly, which is another advantage of our model. Experimental results show that the proposed model can achieve lower entropy than conventional Haar or D5/3 discrete wavelet transform in case of lossless coding.