摘要: 直方图均衡化和匹配,能够智能的提高图像对比度,而编写面向对象的程序可以让图像处理工作提高效率。论文中讨论了图像的均衡化处理原理,即把原始图像的灰度直方图从比较集中的某个灰度区间变换到全部灰度范围内,力求灰度直方图的均匀分布化,也就是对图像灰度空间进行了非线性拉伸,重新分配图像像素值,使一定灰度范围内的像素数量大致相同,以改善了图像质量。但是均衡化使得图像的灰度值减少,甚至细节消失,造成部分图像的对比度过分增强,影响了图像的实际效果。通过直方图均衡化对图像进行处理,能够更好展示图像中的不同细节,对过曝或曝光不足、太亮或者太暗的图像非常有用。设计中运用C#语言对图像按直方图匹配及均衡化,改善了图像细节,使图像更加清晰美观。6712
关键词: BMP;灰度图像;直方图;均衡化;匹配。
Designed Program of Matching and Equalization Based on Gray Image Histogram
Abstract: Image contrast can be enhanced intelligently by matching and equalization based on histogram. The object-oriented programs are designed which can make image processing efficiently. In the passage, principle of equalization based on image processing is discussed, that is, the gray histogram of the original image transformation from the concentration gray interval to the entire gray level range in order to distribute gray histogram equally. The images of gray space are stretched nonlinearly, redistributing image pixel values, making the number of pixel gray level range the same in order to improve the image quality. But grey value of images are decreased or disappeared by equalization which cause part of the image contrast enhance, influencing the infection of images. According to processing images by histogram equalization that can be able to display images in different details for exposure, underexposure, too bright or too dark images, which is very useful. Images are designed by using the C# language of matching and equalization based on histogram are improved the image detail that make the image more clear and beautiful.
Keywords: Bitmap; Gray image;Histogram;Equalization;Matching.
目录
摘要 i
Abstract i
目录 ii
1 数字图像处理概述 1
1.1 数字图像技术综述 1
1.1.1 图像技术 1
1.1.2 数字图像 2
1.2 BMP图像结构 3
1.2.1 BMP文件组成 3
1.2.2 BMP的存储算法 5
1.3 C#语言基础 5
1.3.1 面向对象的C#语言 5
1.3.2 C#的图像处理基础 6
2 直方图均衡化和匹配原理 7
2.1 数字图像 7
2.2 直方图均衡化原理与算法 8
2.2.1 线性点运算 8
2.2.2 直方图灰度拉伸 8
2.2.3 灰度图像直方图均衡化 9
2.2.4 灰度直方图均衡化算法 10
2.3 直方图匹配处理原理与算法 11
2.3.1 灰度图像的直方图匹配 11
2.3.2 灰度图像的直方图匹配算法 12
3 灰度图像的直方图程序设计 14
3.1 Bitmap类设计 14
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