混合编码图像感兴趣区域无损压缩算法研究

Research on ROI Lossless Compression Algorithm for Mixed Coding Images

针对包含重要局部信息图像的高压缩比压缩问题,文章对基于改进EZW和Huffman混合编码的感兴趣区无损压缩算法进行了研究,该算法可以保证感兴趣区无损解码还原,并得到整幅图像的高压缩比压缩。相对其它压缩方法,该算法同时较好的解决了压缩比低与重要信息损失的问题。文章采用Lena女孩图像进行实验,在保持其眼睛信息不损失情况下对整体图像进行高压缩比压缩,最后给出了算法实现的流程图,不同码率情况下的压缩比、压缩解压时间以及峰值信噪比PSNR的比较。实验结果显示,编码和解码时间效率高,压缩效果理想。

The authors research on ROI （Region of Interest） lossless compression algorithm for blended coding images based on improved EZW and Huffman, to solve the problem of high compression ratio of images containing important regional information. This algorithm will ensure ROI lossless decoding and high compression ratio of the whole image. It solves low compression and loss of important information compared with other methods, We finish the experiment on the photo of Lena, compressing the whole image highly without loss of eye information. Finally we list the chart flow of trois algorithm, and the comparison of compression ratio, compression ＆ decompression time and PNSR under different bppo We get a good result of compression with a high time efficiency of coding and decoding from the experiment.