Matlab微光图像去噪技术研究与实现

摘要微光成像的原理是通过一个像增强器，对在夜间或低照度情况下获取的图像进行处理，实现在低照度下观察的目的。在获取微光图像的过程中，通常会产生各种噪声。不同的去噪方式适用于不同的噪声，产生的效果也不同。图像经过去噪处理后，能提高清晰度，获取更多细节信息。微光图像去噪技术的研究有着十分重要的意义。
以当前的小波理论和小波去噪的相关技术研究为基础，本文介绍了小波法在图像去噪领域的应用。对常用的几种小波去噪方法进行了阐述，着重分析了小波阈值去噪法，针对不足改进了阈值和阈值函数的选取。本文用Matlab进行仿真实验分析，通过将空域相关滤波方法和小波阈值法结合，克服各自的缺点，改善了去噪效果和客观指标，得到了较好的仿真效果。25133
关键词微光图像小波图像去噪阈值
Title Research and Implementation of LLL Image Denoising Technology
Abstract
Low light level (LLL) imaging is based on converting images, which areachieved
at night or in low light level, by an image intensifier to enhance the details
in the image and achieve clear observation in low light level. With the LLL imaging,
a lot of noise will be produced simultaneously. There are several different kind
of de-noise methods, whichare proposed for different kind of noise, and their
de-noise effects are not the same. The de-noised images have higher clarity and
we can get much more detail information from them. Therefore, there is a
greatsignificance to improve LLL image de-noising technology.
Based on the current wavelet de-noising and wavelet theory related technology
research, we presented the application of wavelet image de-noising method. Several
general wavelet de-noising methods are studied and we emphatically discussed the
wavelet threshold method. In order to address its shortcomings, several threshold
selecting strategies and threshold functions are presented. In this paper, we use
Matlab software to simulate the wavelet de-noising experiments. Threshold
selecting strategy and threshold function are improved, overcoming the
discontinuous character of the hard threshold method and large de-noising errorof
the soft threshold method. The experimental results demonstrate that our proposed
method can achieve better de-noising effect and obtain high-quality de-noised LLLimages.
Keywords LLL Image Wavelet Image De-noising Threshold
目次
1 引言1
1.1 选题背景与研究意义.. 1
1.2 国内外研究现状. 1
1.3 本文内容安排.. 2
2 小波变换基本理论3
2.1 傅里叶变换和短时傅里叶变换. 3
2.2 小波变换. 4
2.3 本章小结. 8
3 小波阈值去噪研究9
3.1 小波阈值去噪原理 9
3.2 阈值函数选取.. 9
3.3 阈值选取.. 10
3.4 本章小结.. 12
4 小波去噪实现和仿真结果分析..13
4.1 空域去噪实现和效果 14
4.2 小波阈值去噪实现和效果 17
4.3 本章小结. 22
结论23
致谢24
参考文献..25
1 引言
1.1 选题背景与研究意义
光电成像技术主要分为红外成像和微光成像两大方向。微光成像的基本原理是使用像增
强器增强获取的微光图像，对图像处理后，获取更多信息。优点是不依赖人造光源照明，而
是利用夜天光辐射的被动照明，因此，它能在观察对方的同时而隐藏自己。微光器件的核心
是像增强器，经过几代的发展，像增强器的性能有了很大进步，但在光电阴极灵敏度和微通
道板分辨力两方面仍需要提高[1]
。
在获取微光图像的过程中，通常会产生各种噪声。来自电路内部的信号扰动称为噪声， Matlab微光图像去噪技术研究与实现:http://www.youerw.com/tongxin/lunwen_18771.html