Wavelet image coding using trellis coded space-frequency quantization

Recent progresses in wavelet image coding have brought the field into its m aturity, Major developments in the process are rate-distortion (R-D) based wavelet packet transformation, zerotree quantization, subband classificatio n and trellis-coded quantization, and sophisticated context modeling in ent ropy coding, Drawing from past experience and recent insights, we propose a new wavelet image coding technique with trellis coded space-frequency quan tization (TCSFQ). TCSFQ aims to explore space-frequency characterizations o f wavelet image representations via R-D optimized zerotree pruning, trellis -coded quantization, and context modeling in entropy coding. Experiments in dicate that the TCSFQ coder achieves twice as much compression as the basel ine JPEG coder does at the same peak signal to noise ratio (PSNR), making i t better than all other coders described in the literature [1].