Enhanced wavelet-based zerotree coding of images

Abstract only given. This paper presents a wavelet based image coding method achieving high levels of compression. Our eigen-designed quadrature mirror filters are implemented in a multi-resolution subband decomposition system. Symmetrical extension and windowing of the multi-scaled subbands are incorporated to minimize the boundary effects. Next, the embedded zerotree wavelet (EZW) coding algorithm is used for data compaction. In our experiments, the EZW coded stream can be further reduced to yield a smaller symbol string by not coding the zero symbol in the last three subbands of the wavelet map, i.e. HL1, LH1, and HH1 which leads to an improved EZW algorithm. Additional compression is obtained with an adaptive arithmetic coder. Results of coding Lena are tabulated. For a low PSNR of 27.69 dB at a bit rate of 0.8554 for the aerial image, the quality of the decoded image is visually acceptable. No blocky effects are evidenced as compared to the JPEG coding technique.