An image coding scheme using SMVQ and support vector machines

To efficiently compress images, the spatial relations among image blocks to achieve low bit-rate compression has been widely adopted in these years. An example of using such spatial relations is side-match vector quantization (SMVQ). In this paper, a new technique utilizing support vector machines (SVM) to enhance the quality of images compressed by an algorithm based on SMVQ is proposed. We incorporate SVM as a part of the encoder/decoder to detect the edges across boundaries and, therefore, to further improve the accuracy in the block predicting phase, while the number of codewords available in the state codebooks can be enlarged at the same time without increasing the bit-rate. Our simulation confirms the superiority of the proposed scheme. Reasonable improvements in the resulting images were also obtained.