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].