What's your sign?: efficient sign coding for embedded wavelet image coding

Wavelet transform coefficients are defined by both a magnitude and a sign. While promising algorithms exist for efficiently coding the transform coefficient magnitudes, current wavelet image coding algorithms are not efficient at coding the sign of the transform coefficients. It is generally assumed that there is no compression gain to be obtained from entropy coding of the sign. Only recently have some authors begun to investigate this component of wavelet image coding. In this paper, sign coding is examined in detail in the context of an embedded wavelet image coder. It is shown that PSNR improvements of up to 0.7 dB are possible from an efficient modeling and entropy coding of the coefficient signs, combined with a new extrapolation technique, which is used to improve the final estimate of insignificant coefficients. These sign coding techniques are applicable to any genre (e.g., zero-tree, context-model) of the embedded wavelet image coder.