两种常用编码方法的研究及C#实现

图像压缩是数字图像处理的一项重要技术。论文研究了基于统计特性的两种熵编码图像压缩编码方法——香农编码和哈夫曼编码，并以C#为工具，对两种编码方法进行实验及对比。实验表明，哈夫曼编码的编码效率远高于香农编码。香农编码占用的存储空间较大，单位码长表达的信息量少；哈夫曼编码节省存储空间，单位码长表达了更为丰富的信息量。

Research and C # Implementation on Shannon Coding and Shannon-Fannon Coding Methods

Image compression is an important technology for digital image processing. In this paper two kinds of entropy code image compression methods which are based on their statistical characters are studied, including Shannon and Huffman. Then, experimental and comparisons are made for the two methods by C#. Experiments show that Huffman coding efficiency is much higher than Shannon coding. Shannon coding occupies more storage space and unit code length expresses less abundant amount of information. Huffman coding occupies less storage space and unit code expresses more information.