Adaptive scanning methods for wavelet difference reduction in lossy image compression

This paper describes methods for adapting the scanning order through wavelet transform values used in the wavelet difference reduction (WDR) algorithm of Tian and Wells (1996). These new methods are called adaptively scanned wavelet difference reduction (ASWDR). ASWDR adapts the scanning procedure used by WDR in order to predict locations of significant transform values at half thresholds. These methods retain all of the important features of WDR: low-complexity, region of interest, embeddedness, and progressive SNR. They improve the rate-distortion performance of WDR so that it is essentially equal to that of the SPIHT algorithm of Said and Pearlman (1996) when arithmetic compression is not employed. When arithmetic compression is used, then the rate-distortion performance of the ASWDR algorithms is only slightly worse than SPIHT. The perceptual quality of ASWDR images is clearly superior to SPIHT