A new subsampling-based predictive vector quantization for image coding

摘要

Improving coding efficiency for vector quantization (VQ), e.g., reducing bit-rate attainable and increasing encoding speed, has attracted intensive attention. A new image VQ scheme of subsampling-based predictive vector quantization (SB-PVQ) is introduced for this aim, which fully exploits the neighboring-pixel smoothness in both intra-blocks and the boundary areas of inter-blocks. Firstly, all non-overlapped image blocks partitioned in an image are down-sampled two-dimensionally periodically. The sub-sampled blocks (sub-vectors) are then vector quantized with a lower-dimensional and smaller size of codebook, which will contribute to speeding up the VQ encoding and reducing the bit-rate. Finally, the original image blocks are constructed with decimated pixels predicted by their intra- or inter-block neighboring subsampled pixels. It should be highlighted that in the sub-block VQ encoding, multiple-candidates scheme is employed for each input in order to find the corresponding sub-codevector that can generate the best reconstructed image block. Compared with the peripheral prediction method, the new method achieves significant improvement in terms of rate-distortion performance while maintaining comparable computation complexity.