基于自适应提升小波变换的图像压缩算法

提出了一种自适应提升小波变换算法,该算法是根据待分析信号的局部特点,自适应的选择更新器,自适应更新器的选择,主要是保持图像边缘不被平滑,防止出现大的小波系数。为确保系统的稳定性,又提出了采用先更新后预测的提升结构。在此结构中,预测过程不影响更新过程,这也为自适应算法的重构提供了有利条件,由于稳定性高、高频系数小以及能够完全重构,使得此方法有利于压缩性能的提高。通过实验证明了该算法的有效性。

Image Compression Algorithm Based on Adaptive Wavelet Transforms Via lifting

The adaptive wavelet transforms via lifting is proposed. Update filter is selected by the partial signal＇s character. The goal of selecting update filter is to prevent the image edge＇s Smoothness and hold small wavelet coefficients. To make sure the system＇s stability, in the lifting scheme of adaptive wavelet, update step is placed before prediction step. In this framework, prediction step doesn＇t affect update step, so it is favorable to reconstruction. The Adaptive wavelet trans- forms via lifting is benefit for the image compression, because of the high stability, the small coefficients of high frequency parts, and the perfect reconstruction. The Effectiveness of the algorithm is proved by experiments.