Progressive Image Transmission Using LOT with Two-Channel Conjugate VQ

Abstract

A progressive image transmission (PIT) scheme based on the classified two-channel conjugate VQ (TCCVQ) technique in the lapped orthogonal transform (LOT) domain is proposed. Conventional block transform coding of images using DCT produces in general undesirable block-artifacts at low bit rates. In this paper, image blocks are transformed using the LOT and classified into four classes based on their structural properties and further subdivided adaptively into subvectors depending on the LOT coefficient statistics to improve the reconstructed image quality by adaptive bit allocation. The subvectors are quantized using the two-channel conjugate VQ technique which has less computational complexity and less storage memory, and is more robust against channel errors. The vector quantized subvectors are transmitted and decoded in stages so that an image is progressively reconstructed, i.e., initially a crude version followed by quality build up in successive stages as the occasion demands in interactive visual communications. Coding tests using computer simulations show that the LOT/TCCVQ-based PIT of images is an effective coding scheme. The results are also compared with those obtained using conventional classified VQ in both the DCT and LOT domains.