A New Adaptive Interframe Transform Coding using Directional Classification

Interframe transform coding is affected not only by the statistics of spatial details within a frame, but also by the variation of the amount of movement and other temporal activities in different regions of the image sequence. Therefore, adaptive techniques have to be used in order to achieve good image quality. In this paper, we propose a new version of the adaptive interframe coding method, namely directional classification, which is based on image sequence statistics. Blocks with different perceptual features such as edges and high motion activity are categorized to different classes. Then, a new adaptive quantization, associated with appropriate scanning and huffman coding, are employed based on the classification map. Coding tests using computer simulation show this technique is indeed very efficient.