Artifact reduction of compressed color images using modified mean‐removed classified vector quantization

In this paper, a new artifact reduction algorithm for compressed color images using MMRCVQ is proposed. The algorithm extends and modifies vector quantization (VQ) for discovering the relationships between the uncompressed color images and their deblocked compressed versions by classifying the deblocked compressed blocks into several categories using information from their neighboring blocks. The discovered relationships are stored in two codebooks and are used to recover the missing information of compressed color images. To increase the availability of codewords and reduce the memory needed for storing codewords, mean‐removed vectors are used to generate codebooks. The experimental results show that the proposed approach can remove, effectively, the artifacts caused by high compression and improve perceptual quality significantly. Compared to existing methods, the proposed approach usually uses much less computing time to recover a compressed color image and has much better image quality.