复杂光照条件下图像自适应增强需要图像处理的其重要组成部分，传统的复杂光照条件下图像自适应增强方法对于改善图像质量发挥了其重要作用。随着对图像技术研究的不断深入和发展，新的复杂光照条件下图像自适应增强方法不断出现。传统的复杂光照条件下图像自适应增强方法基本可以分为空域复杂光照条件下图像自适应增强方法和频域复杂光照条件下图像自适应增强方法两大类。空域是指组成图像的像素的集合，空域复杂光照条件下图像自适应增强直接对图像中像素灰度值进行预算处理，如灰度变换、直方图均衡化、图像的空域平滑和锐化处理、位彩色处理等。
小波多分辨分析由于它能多尺度多角度提取信号特征，往往可在不同尺度上噪声和信号明显地区分开来，所以它在图像去噪和增强方面有很大优势。本文提出的基于小波技术的梯度增强方法的基础上，通过增加灰度数量和增强图像的灰度对比度，取得了较好的增强效果。针对不同特点的图像采用相应的复杂光照条件下图像自适应增强方法可以达到较好的增强效果。实验结果表明，本文提出的改进方法对于某些图像取得了比传统的增强方法更好的效果。
关键词：图像处理；直方图；复杂光照条件下图像自适应增强；直方图均衡；小波变换
Abstract
Image adaptive enhancement under complex lighting conditions requires an important part of image processing. Image adaptive enhancement method under traditional complex illumination conditions plays an important role in improving image quality. With the deepening and development of image technology research, the image adaptive enhancement method is emerging under the new complex illumination condition. Under the traditional complex illumination conditions, the image adaptive enhancement method can be divided into two parts: image adaptive enhancement method and image adaptive adaptive enhancement method under complex light conditions under complex lighting conditions. The spatial domain refers to the set of pixels that make up the image, and the image adaptive enhancement under the condition of the complex space of the airspace directly prepares the gray value of the pixel in the image, such as gray scale transformation, histogram equalization, image space smoothing and sharpening, Bit color processing.
Wavelet multiresolution analysis Because of its ability to extract signal features from multiple scales, it is often possible to distinguish noise and signals at different scales, so it has a great advantage in image denoising and enhancement. Based on the gradient enhancement method proposed in this paper, the enhancement effect of the gray scale and the gray scale contrast of the enhanced image is obtained. The image enhancement method can achieve better enhancement effect under the corresponding complex illumination conditions for different characteristics of the image. The experimental results show that the improved method proposed in this paper has a better effect on some images than traditional enhancement methods.
Key words: image processing; histogram; image enhancement under complex lighting conditions; histogram equalization; wavelet transform
目 录
1 绪 论 1
1.1 课题的背景及意义 1
1.1.1 课题的背景 1
1.1.2 研究意义 2
1.2 国内外研究现状与分析 3
1.3 本文研究的主要内容 4
2 复杂光照条件下图像自适应增强算法的原理及实现 6
2.1 直方图修正 6
2.1.1 直方图均衡化 6
2.1.2 直方图规定化 7
2.2 锐化 8
2.2.1 梯度锐化法 9
2.2.2 拉普拉斯锐化 11
2.3 去噪 12
2.3.1 邻域平均法 12
2.3.2 中值滤波法 14
2.4 灰度变换 15
2.4.1 比例线性变换 15
2.4.2 分段线性变换 17
2.4.3 非线性灰度变换 18
3 复杂光照条件下图像自适应增强算法的原理及实现 20
3.1 低通滤波器 20
3.2 高通滤波器 21
3.3 同态滤波器 22
4 彩色复杂光照条件下图像自适应增强算法的原理及实现 24
4.1 假彩色增强 24
4.2 伪彩色增强 24
4.2.1 密度分割法 24
4.2.2 灰度变换法 26
4.3 真彩色增强 26
5 和频域相结合的复杂光照条件下图像自适应增强算法的研究 29
5.1 低频滤波和拉普拉斯变换、直方图均衡化相结合算法 29
5.1.1 低通滤波 29
5.1.2 拉普拉斯锐化 31
5.1.3 直方图均衡化 31
5.1.4 具体算法及其实现 32
5.2 高通滤波和直方图均衡化相结合算法 33
5.2.1 高频滤波 34
5.2.2 具体算法及其实现 34
结 论 36
参考文献 37
致 谢 38
