小波变换在图像压缩研究中的现状和趋势

Situation and Development of Wavelet Transform Application in Image Compression

小波变换在时域、频域均具有良好的局域化特性，弥补了ＤＣＴ变换的不足，它的多分辨率变换特性与人眼的视觉特性非常接近。小波变换图像压缩编码不仅保持了原图像在各种分辨率下的精细结构，而且便于和其它新兴图像编码方法相结合，成为当令研究的热点。在分析小波变换原理的基础上，讨论了小波变换用于图像压缩的关键技术，并展望其发展前景。

Wavelet transform has good localization properties both in space and frequency domains, which make up the deficiency of DCT. Moreover, it resembles the human visual system (HVS) in that an image is decomposed into multi-scale representation. Wavelet transform has recently emerged as a promising technique for image compression due to its flexibility in multi-scale solution representation of image signals. This paper states the theory of wavelet transform, analyses its key technology and prospects its foreground.