基于DCT的图像压缩/解压缩算法研究

基于DCT的图像压缩/解压缩算法研究(任务书,开题报告,论文13000字)
摘  要
在科技发展的今天，图像信息广泛。但图像的数据量一般都比较大，十分不利于存储和传输。实际应用中，通常需要对图像进行压缩。论文主要研究了按照国际压缩标准JPEG（Joint Photographic Experts Group），并基于DCT（Discrete Cosine Transform）即离散余弦变换的图像压缩和解压缩算法[1]。通过MATLAB及其图像处理工具。论文还详细介绍了编码步骤如，DCT变换、量化、熵编码等模块的原理和数学公式及推导，还有各模块的功能分析。最后应用MATLAB进行实验与仿真并分析结果得出结论。
研究结果表明JPEG图像压缩方法简单方便，是互联网上最普遍的方法之一，其优点在于既能保证压缩比，又能保证图像质量，且MATLAB运行出来的仿真结果较好地反映了其编码算法原理。
关键词：DCT变换；图像压缩算法；MATLAB；JPEG标准

Abstract
In the development of science and technology, the image information is wide. But the amount of image data is generally large, which is very bad for storage and transmission. In practice, image compression is usually required. This paper mainly studies the image compression and decompression algorithm based on the international compression standard JPEG (Joint Photographic Experts Group) and based on the DCT (Discrete Cosine Transform), the discrete cosine transform. By using MATLAB and its image processing tools. The paper also introduces the principles, mathematical formulas and derivation of the coding steps, such as DCT transform, quantization and entropy coding, as well as the functional analysis of each module. Finally, MATLAB is used to carry out experiments and simulations, and conclude the results.
The results show that the JPEG image compression method is simple and convenient. It is one of the most common methods on the Internet. Its advantage is that it can not only guarantee the compression ratio, but also guarantee the quality of the image. And running the simulation results of the MATLAB reflects the principle of the coding algorithm well.

Key Words：DCT transform；Image compression algorithm；MATLAB；Joint Photographic Experts Group
 
目录
第一章 绪论    1
1.1基于课题的深入研究    1
1.2 数字图像处理    3
1.2.1 数字图像处理内容    3
第二章 图像处理基本原理    5
2.1图像压缩基础    5
2.2 JPEG标准    5
2.2.1颜色模式转换及分块采样    6
2.2.2离散余弦变换    7
2.2.3 DCT系数量化    8
2.2.4 Z字排列    11
2.2.5 熵编码    12
2.3 图像解压缩    14
2.3.1 反量化 反DCT变换 颜色转换    15
第三章 实验仿真及结果    16
3.1 仿真结构    16
3.2 MATLAB函数    16
3.2.1 图像的读入和输出    16
3.2.2 图像转换    17
3.2.3 DCT变换实现    19
3.2.4 Z型扫描的实现    20
3.3 仿真结果图象    20
3.4 实验结果分析    23
第四章 总结与展望    24