红外图像盲元补偿算法研究

红外图像盲元补偿算法研究(论文12000字)
摘要：红外成像技术是一种发现、探测和识别目标的重要手段，能够应用于众多领域，如工业、消防、医疗等。然而，由于红外探测器本身、光学系统以及探测环境的影响，红外成像的效果并不是很理想，盲元问题在红外焦平面阵列成像过程中仍无法避免。这个问题在很大程度上使得成像系统的空间和温度分辨率降低，严重影响成像系统的性能。因此，在对红外图像的处理中解决盲元问题是不可或缺的步骤。其中，盲元补偿是解决盲元问题的关键。
本文首先对红外成像原理进行了分析，在此基础上研究了盲元定义和分类，并总结其产生原因、灰度特性以及对红外系统的影响。然后研究了几种典型的红外盲元补偿算法，包括邻元替代法、邻域平均算法和中值滤波算法，通过实验总结了它们的优缺点。最后基于目前算法缺乏对红外图像的适应性，容易造成图像细节模糊的缺点，本文提出从多尺度分析的角度处理盲元，同时将自适应回归模型引入补偿算法，并将其与现有的盲元补偿算法对比。实验证明，本文算法对红外图像有很好的适应性，可以达到较好的补偿效果。
关键词：红外图像；盲元补偿；自适应回归

Research on blind element compensation algorithm for infrared image
Abstract:Infrared imaging technology is an important means of discovering, detecting and identifying targets, which can be used in many fields, such as industry, fire fighting and medical treatment. However, due to the influence of infrared detector, optical system and detecting environment, the effect of IR imaging is not very ideal, and the blind element problem is still unavoidable in IR focal plane array imaging process. This problem has greatly reduced the space and temperature resolution of imaging system, which seriously affects the performance of imaging system, so it is necessary to solve the problem of blind element in IR image processing.
The blind element compensation is the key to solve the blind element problem. Firstly, this paper analyzes the structure principle of IR imaging system, and introduces the definition and classification of blind elements, and summarizes the causes, the gray character and the influence on IR system. Then, some typical infrared blind element compensation algorithms are studied, and their advantages and disadvantages are compared. Finally, based on the present algorithm lacks the adaptability to the infrared image, which is apt to cause the blurred image detail, this paper considers the blind element from the angle of multi-scale analysis, and introduces the adaptive regression model to the compensation algorithm, and compares it with the existing blind element compensation algorithm. Experimental results show that the proposed algorithm has a good adaptability to IR image and can achieve better compensation effect.
Key words:Infrared image；Blind pixel restoration；Adaptive Regression
 

目录
1 绪论    1
1.1 研究背景及意义    1
1.2 国内外研究现状    1
1.3 本文的组织结构    2
2 红外成像系统及盲元分析    3
2.1 红外成像系统概述    3
2.2 红外图像的特点    3
2.3 盲元问题分析    4
2.3.1 盲元的定义及分类    4
2.3.2 盲元的产生原因    5
2.3.3 盲元特征分析以及对红外系统的影响    6
2.4 本章小结    6
3 常用盲元补偿算法研究    7
3.1 邻元替代法    7
3.2 邻域平均法    7
3.3 中值滤波法    10
3.4 本章小结    12
4 基于自适应回归的盲元补偿算法    13
4.1 自适应回归原理    13
4.1.1 参数回归    13
4.1.2 非参数回归    14
4.2 基于自适应回归模型的盲元补偿算法    16
4.3 算法实现步骤    17
4.4 实验结果及分析    18
4.5 本章小结    19
5 总结与展望    20
参考文献    21
致谢    22