Image coding based on integer wavelet and embedded optimal coefficient scaling  

作　　者：张立保 杨凯娜 

机构地区：[1]College of Information Science and Technology, Beijing NormM University, Beijing 100875, China [2]State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China

出　　处：《Chinese Optics Letters》2012年第B06期97-100,共4页中国光学快报（英文版）

摘　　要：Integer wavelet transform （IWT） could offer the lower computational complexity and the less storage spending for image compression than the discrete wavelet transform （DWT）. But the most coefficients of the IWT image have smaller dynamic change ranges than discrete wavelet transform. In this letter, an efficient and low-complerity coding algorithm called embedded optimal coefficient scaling （EOCS） is proposed. It optimizes the distribution of the wavelet coefficients in every threshold plane and provides an efficient embedded quadtree-partitioning scheme to encode the image. Experimental results show that the presented method cannot provide peak signal-to-noise ratio （PSNR） performance up about 2~6 dB better than set partitioning in hierarohical trees （SPIHT） without the OCSF scheme, but also support both efficiently lossy and lossless compression in single bitstream.Integer wavelet transform （IWT） could offer the lower computational complexity and the less storage spending for image compression than the discrete wavelet transform （DWT）. But the most coefficients of the IWT image have smaller dynamic change ranges than discrete wavelet transform. In this letter, an efficient and low-complerity coding algorithm called embedded optimal coefficient scaling （EOCS） is proposed. It optimizes the distribution of the wavelet coefficients in every threshold plane and provides an efficient embedded quadtree-partitioning scheme to encode the image. Experimental results show that the presented method cannot provide peak signal-to-noise ratio （PSNR） performance up about 2~6 dB better than set partitioning in hierarohical trees （SPIHT） without the OCSF scheme, but also support both efficiently lossy and lossless compression in single bitstream.

分 类 号：TN919.81[电子电信—通信与信息系统] TP391.41[电子电信—信息与通信工程]