How Can Intra Correlation Be Exploited Better?

Summary form only given. This paper studies how to better exploit intra correlation to compress images. In general, edge and texture areas of images exhibit strong anisotropic property. The correlation among samples is determined by not only their distance but also the link orientation. Traditional transforms are not efficient on handling this anisotropic correlation. Therefore, in this paper we propose a directional filtering transform (dFT, in order to distinguish from the common usage on DFT) to exploit local anisotropic correlation among samples. Similar to directional prediction in H.264 intra-frame coding, but it adopts the hierarchal structure to decrease the distance between samples to be predicted and that are used for prediction. From another viewpoint, the dFT prediction resembles the directional wavelet transform without update, which can take both intra-block and inter-block correlations into account.