基于整数小波变换和子带比特平面编码的图象压缩算法

A Scalable Image Compression Scheme Based on Integer-to-integer Wavelet Transform and Subband Bit-plane Coding

在分析图象整数小波变换的基础上 ,提出了基于子带比特平面编码的压缩算法 .该算法将整数小波系数按子带分为若干比特平面 ,称之为子带比特平面 ,并采用简单高效的率失真优化算法确定子带比特平面的编码顺序 ,且这一顺序与图象无关 .按此顺序对子带比特平面进行自适应 MQ算术编码 ,便得到嵌入式压缩码流 .该算法可以从无损到有损 ,以任意倍率或质量进行图象压缩 ,压缩效率达到了浮点 EZW算法和 JPEG2 0 0 0整数小波编码方案的水平 ,而速度远快于这两者的速度 .该算法还具有复杂度低 ,占用内存少的优点 .

This paper provides an image compression scheme called SBPC algorithm based on subband bit plane coding and integer to integer wavelet transform. SBPC algorithm divides the coefficients of integer to integer wavelet transform into bit planes within each subband which are named as subband bit planes. For these subband bit planes, the algorithm uses simple but effective rate distortion optimization method to determine the coding order. Unlike the JPEG2000 standard, this R D optimized coding order is independent of images. According to the coding order , the coefficient bits are coded by adaptive MQ arithmetic coder. SBPC algorithm can compress an image at any given bit rate or image quality from lossless to lossy, and the coding stream is scalable both in spatial resolution and in image quality. The algorithm can also realize coding of images with region of interest(ROI) by compressing the ROI losslessly. The experiments show that SBPC algorithm is comparable to the float point EZW algorithm and JPEG2000 reversible coding scheme in the coding efficiency, while the coding/decoding speed is much faster than that of the other two algorithms. In addition, SBPC algorithm needs very low memory and its computation complexity is also low.