Unequal error protected ROI image transmission based on vector quantization

In this paper we propose novel progressive scalable region of interest (ROI) image compression schemes with rate, distortion, and complexity trade-off based on vector quantization. The proposed schemes are unbalanced in the sense that the decoder has less computational requirements than the encoder. Moreover, the proposed method provides an interactive tool for fast ROI based browsing from image archives. Residual vector quantization (RVQ) equips the encoder with a multi-resolution apparatus which is useful for rate-distortion trade-off. Having all advantages of RVQ, jointly sub-optimized RVQ provides a distortion-complexity adjustment. Since the bitstreams associated with the earlier stages of the RVQ encoder are more important for the reconstructed image quality than that of the later stages, an unequal error protection scheme, base on Reed-Solomon codes, has been considered to protect the transmitted bitstream against channel noise.