文档介绍：分类号: 密级:
U D C : 编号:
工学硕士学位论文
红外图像非均匀性校正和增强技术研究
分类号: 密级:
U D C : 编号:
工学硕士学位论文
红外图像非均匀性校正和增强技术研究
Classified Index:
:
A Dissertation for the Degree of M. Eng
Research on Infrared Image Non-uniformity Correction and Image Enhancement Technology

摘要
由于红外成像系统具有抗干扰性能强、目标识别能力强、被动工作等特点,已被广泛的应用于军事和民用领域,是具有广阔发展前景的一种成像技术。因此,研制出高性能的红外成像系统具有重要的意义。
红外焦平面阵列是成像系统的最重要的器件,它的性能直接影响着整个系统的运行。但是,受到当前技术水平和工艺水平的限制,红外焦平面阵列存在严重的非均匀性,并且红外图像具有对比度低、目标与背景区分不明显的缺点,针对红外焦平面阵列存在的这些问题,本文给出了有效的解决方法,主要工作如下:
(1)针对传统基于神经网络校正算法结果存在图像模糊和伪像的问题,本文在分析问题产生原因的基础上,提出了有效的改进算法:使用可变参数非线性滤波器代替原算法中的均值滤波器。改进算法中使用的非线性滤波器参数可以根据局部图像细节信息的不同作相应的变化,校正结果不仅在清晰度方面有明显的改善,而且有效的消除了传统算法中存在伪像的问题。
(2)在分析了盲元产生原因以及盲元与点目标之间区别的基础上,提出了基于二维线性外推理论的盲元检测算法,并在实验中对其进行了验证,有很好的检测效果。
(3)针对红外图像具有整体亮度偏暗、对比度较低、目标与背景区分不明显的特点,结合模糊集理论、灰度变换和多分辨率图像融合等理论,提出了一种新的基于模糊集理论的红外图像增强算法。它在提高图像对比度的同时,能够更好的保留原始图像的细节信息,使得处理后的图像边缘信息更加明显。
通过本文的研究,达到了红外图像非均匀性校正、盲元补偿和图像增强的目的,这也为后续的图像处理和应用打下了坚实的基础。
关键词:红外焦平面阵列;非均匀性校正;盲元补偿;图像增强
ABSTRACT
Infrared imaging system has the characteristic of strong anti-jamming performance ,target recognition capability and also passive work,. It has been widely used in military and civilian fields. The imaging technique has broad prospects for development. So, there is important significance for the development of a high performance infrared imaging system.
Infrared focal plane array is a key part of thermal imaging system. Its performance affects the operation of the system directly. However, limited by current technology, infrared focal plane arrays has the problem of non-uniformity, and infrared images have the features of low contrast; it is hard to distinguish between target and background. This paper presents many effective methods to solve these problems which exist in the infrared focal plane arrays. In this paper, more contexts are given:
(1) The results obtained by traditional work correction algorithm, have the problems of blurring effect and some existing artifacts. After analysis the reasons of th