Robust still image coding using lapped transforms with block classification

Very efficient still image compression methods exist today, but most of them are not fit for transmission on error prone channels. One example of state-of-the-art robust image coding is the use of wavelet compression followed by forward error correction, as proposed by P.G. Sherwood and K. Zeger (see Proc. IEEE Data Compress. Conf, p.72-81, 1997); that method gives high coding efficiency but suffers from the incomplete decoding problem. An alternative to this is the joint source/channel coding scheme by Qing Chen and T.R. Fischer (see IEEE Trans. on Img. Proc., vol.7, no.4, p.496-505, 1998), which overcomes this difficulty at the expense of a lower PSNR performance. We propose a joint source/channel coding scheme with increased coding efficiency based on lapped transforms with block classification. With an efficient bit allocation strategy and the high coding gain of lapped transforms, a significant increase, of the order of 2 dB, in the PSNR versus BER performance has been obtained over the classical joint source/channel scheme on binary symmetric channels.