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摘要近年来随着时代的发展与科学的进步，人类不再满足于日常生活中人眼直接获取的光信息，随即发展图像处理技术成为重要课题，对微光探测和增强方面的研究也越发深入。作为图像处理过程中重要的一步，图像增强技术在整个图像处理和显示过程中起到关键的作用，为图像下一步的高层次处理，分析和显示的做好准备。本文最先介绍对现有微光成像探测器的发展状况，以及微光图像增强的研究背景、应用领域和发展状况。然后主要围绕微光图像增强的基本原理进行展开，着重对直方图变换法、灰度变换法、图像的平滑及锐化等几种图像增强的方法做了具体的介绍。最后运用MATLAB软件对微光图像进行增强处理的算法设计。通过对比成像结果得出各个图像增强算法的优缺点。21360
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关键词 微光探测器 图像增强 灰度变换 直方图变换 平滑 锐化 MATLAB
毕业论文设计说明书（论文）外文摘要
Title New Algorithm of Shimmer Image Enhancement
Abstract
With the development of image processing technology in recent years, more and more in-depth study for low light level detection and image enhancement has been carried out. In the common sense, image enhancement is considered as a simple processing and is in the preprocessing stage. However, it is an important step in image processing, playing an important role in linking the whole image processing and displaying process, and is critical in successfully acquiring high level image processing.
In this paper, recent development of the existing shimmer image detectors as well as the research background, applications and development of shimmer image enhancement are first reviewed. And then based mainly on the fundamental principles of image enhancement, several methods of image enhancement, particularly the histogram transformation, gray-level transformation, image smoothing and sharpening are specifically introduced. By using MATLAB software, the design of a new algorithm for various methods of low light level image enhancement is derived. Finally, the experimental results from various image enhancement methods are compared and the advantages and disadvantages of each method are discussed.
Keywords:Shimmer image detector; image enhancement; gray-scale transformation; histogram transformation; smoothing; sharpening; MATLAB
目 次
1 绪论 1
1.1 选题背景 1
1.2 应用领域 1
1.3 研究与发展状况 2
1.4 本文所做的工作 3
2 图像增强的基本理论 4
2.1 数字图像处理的概述 4
2.2 图像的数字化 4
2.3 图像增强的概述 4
3 图像增强的基本方法和原理 6
3.1 空域增强变化 6
3.2 空域滤波增强 10
3.3 频域增强 13
3.4 色彩增强 15
4 图像增强的MATLAB算法与实现 17
4.1 对比度（灰度）扩展以增强图像 17
4.2 直方图处理 18
4.3 图像间的代数运算 21
4.4 平滑滤波 23
4.5 锐化滤波 26
4.6 低通滤波 27
4.7 高通滤波 29
4.8 RGB颜色空间彩色增强 31
4.9 YUV颜色空间彩色增强 34
结 论 36
致 谢 37