Ding Xu-xing, Zhu Ri-hong, Li Jian-xin. Image Compression Based on Integer Wavelet Transform and Improved Embedded Zerotree Wavelet Encoding[J]. Journal of Electronics & Information Technology, 2004, 26(7): 1064-1069.
Citation:
Ding Xu-xing, Zhu Ri-hong, Li Jian-xin. Image Compression Based on Integer Wavelet Transform and Improved Embedded Zerotree Wavelet Encoding[J]. Journal of Electronics & Information Technology, 2004, 26(7): 1064-1069.
Ding Xu-xing, Zhu Ri-hong, Li Jian-xin. Image Compression Based on Integer Wavelet Transform and Improved Embedded Zerotree Wavelet Encoding[J]. Journal of Electronics & Information Technology, 2004, 26(7): 1064-1069.
Citation:
Ding Xu-xing, Zhu Ri-hong, Li Jian-xin. Image Compression Based on Integer Wavelet Transform and Improved Embedded Zerotree Wavelet Encoding[J]. Journal of Electronics & Information Technology, 2004, 26(7): 1064-1069.
The main advantages of Integer Wavelet Transform(IWT) are that the input and output values are all integers, all operations can be done in place, only a small memory is required and easy to be implemented in hardware. In the context of image coding, IWT is well suited for lossless compression. However, it performs a little worse compared to the conventional Discrete Wavelet Transform(DWT) for lossy compression. In this paper, a new algorithm is proposed for improving lossy compression performance of IWT, It is by means of the IWT based on lifting scheme combining with improved Embedded Zerotree Wavelet(EZW) based on morphological dilation operation. Simulation results show the proposed algorithm improves the Peak Signal Noise Ratio(PSNR) compared to conventional DWT without increasing computational complexity.