基于压缩感知和霍夫曼方法联合压缩核磁共振脑组织图像的处理
首发时间:2012-02-24
摘要:基于无损压缩和有损压缩方法,提出一种针对医学图像压缩的联合压缩方法。使用压缩感知对大脑核磁共振组织图像的非目标区域无损压缩,使用霍夫曼编码对背景区域进行有损压缩。其中,压缩感知的方法,使用小波变换得到稀疏矩阵,使用随机生成的参数为0或1的矩阵作为测量矩阵,使用OMP算法做为重构还原算法。实验结果表明,使用联合压缩的方法,可以将数据压缩为原图像的1/4,相比于传统的霍夫曼编码,在较好地保留了目标区域信息的同时,获得了较高的压缩比。
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Research on CS and Huffman based MRI image Compression
Abstract:Based on Lossy compression and Lossless compression, a combining method for medical image compression was proposed, which compressed losslessly the background area of brain MRI(Magnetic Resonance Imaging) with CS(Compressed Sensing) , and compressed with loss the interested area using Huffman coding. In the CS based compression, Sparse matrix was obtained using wavelet transform, while measurement matrix was a matrix composed by random generated parameters 0 or1. And OMP algorithm was adopted for reconstruction. Experiment results illustrate that the combining method has compressed the image to 1/4 of its origin, which, compared with the traditional Huffman coding method, obtained high compression ratio, at the same time, maintained the information of interested area.
Keywords: Lossy compression Lossless compression MRI Image compression
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