基于MATLAB的哈夫曼编码的图像压缩的实现
基于MATLAB的哈夫曼编码的图像压缩的实现
[内容摘要]本文通过对图像压缩的介绍以及对哈夫曼算法实现的探讨，基本阐明了图像压缩概况以及哈夫曼编码实现的算法，对于实现算法主要参照了A. Moffat和J. Katajainen设计空间复杂度最小的的在权值数组内部构建Huffman的方法以及范氏哈夫曼编码方法这些优秀的算法，在MATLAB 6.5环境下进行了编程，实现了对灰度图像的压缩和解压缩，得出平均码长为7.47,与熵值7.44十分接近，同时求出压缩比率约为1.07，译码所得的矩阵f1和原图像灰度级值矩阵f相等，说明了是无失真的压缩，同时也验证了解码的正确性。
[关键词] 范氏哈夫曼编码；模拟构建哈夫曼树；图像压缩；MATLAB；映射
[ABSTRACT] Based on the presentations and huffman algorithm, explained the basic profile of image compression and huffman encoding algorithm.The main algorithm are In-Place Calculation of Minimum-Redundancy Codes by A. Moffat and J. Katajainen and Canonical Huffman Encoding. According to these algorithm,in MATLAB 6.5 environment, using the matlab programming language, a gray-scale image compression was achieved.Solving out the average length of code is 7.47 is very close to entropy value 7.44, calculated compression ratio is about 1.07. Decoding matrix f1 and original gray-level image f are equal value ,that is a lossless compression. also verify the correctness of the decoder.
[KEY WORDS] Canonical Huffman Encoding; In-Place Calculation of Minimum-Redundancy Codes;image compression ;MATLAB;Mapping
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