Image Coding Using Optimized Signi cance Tree Quantization Geo rey

A number of recent embedded transform coders, including Shapiro's EZW scheme, Said and Pearlman's SPIHT scheme, and Xiong et al.'s EZDCT scheme employ a common algorithm called signi cance tree quantization (STQ). Each of these coders have been selected from a large family of signi cance tree quantizers based on empirical work and a priori knowledge about transform coe cient behavior. We describe an algorithm for selecting a particular form of STQ that is optimized for a given class of images. We apply our optimization procedure to the task of quantizing 8x8 DCT blocks. Our algorithm yields a fully embedded, low-complexity coder with performances from 0.6 to 1.9 dB better than baseline JPEG for standard test images.