MATLAB课设报告-基于MATLAB的图像处理的基本运算.doc

MATLAB课设报告-基于MATLAB的图像处理的基本运算.doc

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基于MATLAB的图像处理数字图像处理技术是20世纪60年代发展起来的一门新兴学科,随着图像处理理论和方法的进一步完善,使得数字图像处理技术在各个领域得到了广泛应用,并显示出广阔的应用前景。MATLAB既是一种直观、高效的计算机语言,同时又是一个科学计算平台。它为数据分析和数据可视化、算法和应用程序开发提供了最核心的数学和高级图形工具。根据它提供的500多个数学和工程函数,工程技术人员和科学工作者可以在它的集成环境中交互或编程以完成各自的计算。 MATLAB中集成了功能强大的图像处理工具箱。由于MATLAB语言的语法特征与C语言极为相似,而且更加简单,更加符合科技人员对数学表达式的书写格式,而且这种语言可移植性好、可扩展性强,再加上其中有丰富的图像处理函数,所以MATLAB在图像处理的应用中具有很大的优势。MATLAB ABSRACT Digital image processing technology is developed in 20th century, 60 years a new discipline, with the image processing theory and methods to further improve, making the digital image processing technology in various fields has been widely applied, and shows a broad prospect. MATLAB is both an intuitive and efficient computer language, but also a scientific computing platform. It provides data analysis and data visualization, algorithm and application development provides the core mathematics and advanced graphical tools. It offers more than 500 according to mathematical and engineering functions, engineers and scientists can be integrated in its environment or programming interaction in order to complete their calculations. MATLAB integrates powerful image processing toolbox. Characteristics of the MATLAB language syntax is very similar with the C language, and more simple, more in line with scientific and technical personnel of mathematical expressions written format, and the portability of this language is good, scalability, coupled with a wealth of images which handler, so the application of MATLAB in image processing has a great advantage. MATLAB for Image Processing Based on the basic operation of the first image brightness and contrast adjustment, rotation, scaling and other operations, then the image is the histogram statistics and histogram equalization, and finally joined a variety of image noise and the the denoising. Key words: digital image processing, MATLAB 目 录 1 绪论 1 1.1 数字图像处理简介 1 1.2 MATLAB简介 2 2 图像的获取 5 2.1 图像的读取与保存 5 3 图像的处理 7 3.1 图像的亮度和对比度调整 7 3.1.1 图像的亮度调整 7 3.1.2 图像的对比

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