Matlab毫米波辐射图像噪声分析与处理技术
最后运用均值滤波、中值滤波、高斯滤波、小波去噪等方法，将辐射图像进行去噪的处理。这几种去噪的方法得到的结果不尽相同。以下是几种图像去噪方式及其效果：
（1）均值滤波：处理后的图像比原图平滑了很多,然而景物轮廓也变得不清晰；
（2）中值滤波：处理后的图像原辐射图像中的噪声被去除了，但依然还是残留有部分难以去除的噪声，但是相较于均值滤波，图像明显变得清晰了。
（3）高斯滤波：图像的边缘模糊，细节不够清楚，整体处理的效果不是很理想。
关键词 被动毫米波成像技术 Matlab 均值滤波 中值滤波 高斯滤波
毕业论文设计说明书外文摘要
Abstract
The acquisition and image processing of millimeter wave radiation signal is one of the main directions of the development of millimeter wave technology.The millimeter wave radiometric imaging technology is widely used in many high - tech fields.Such as remote sensing, military, public safety, environmental detection, etc.This paper mainly uses Matlab software to simulate some millimeter wave radiometric images, and analyzes the results.In this paper, the theory of passive millimeter wave imaging is introduced firstly, then the principle of millimeter wave imaging system is introduced.
Finally,using the mean filter, median filter, Gauss filter,and wavelet denoising methods to process the Noise of the radiation image.The results of these denoising methods are different.The following are several image denoising methods and their effect:
(1)Mean filtering:The image processed smoother than the original one, but the scenery outline become ont clear;
(2)Median filtering:The noise in the original image is removed.But there is still a part of noise which is hard to remove,But the image is clearer than the one which is processed by mean filter.
(3)Gauss filtering:The edge of the image is vague, the details are not clear and the effect of the whole process is not very ideal.
Keywords Passive imaging Matlab Mean filtering Median filtering Gauss filtering
目 次
1 绪论 1
1.1 毫米波的特点 1
1.2 被动毫米波成像技术理论以及发展历史 1
1.3 毫米波辐射计 3
1.4 被动毫米波图像的处理的意义 4
1.5 本文内容安排 4
2 毫米波辐射成像系统 6
2.1 成像体制 6
2.2 被动毫米波成像系统的原理框图 6
2.3 毫米波辐射成像的物理原理 7
2.4 毫米波成像的原理 7
2.5 辐射计成像系统的技术指标 9
2.6 毫米波辐射成像分析 11
3 毫米波辐射成像的几种处理方法 13
3.1 引言 13
3.2 邻域平均法 13
3.3 中值滤波法 13
3.4 小波去噪增强 15
4 被动毫米波辐射图像上的噪声去除 19
4.1 灰度直方图 19
4.2 均值滤波 21