基于人眼视觉的红外图像增强算法研究  

Infrared image enhancement algorithm based on human vision

作　　者：王晨[1,2] 汤心溢[1] 高思莉[1] WANG Chen TANG Xin-yi GAO Si-li(Shanghai Institute of Technical Physics, CAS, Shanghai 200083, China University of Chinese Academy of Sciences, Beijing 100049, China)

机构地区：[1]中国科学院上海技术物理研究所,上海200083 [2]中国科学院大学,北京100049

出　　处：《激光与红外》2017年第1期114-118,共5页Laser & Infrared

基　　金：上海物证重点实验室基金(No.2011xcwzk04);国家"十二五"国防预研项目(No.41101050501)资助

摘　　要：红外图像具有低对比度、噪声大、动态范围大以及视觉效果差等特点。传统的图像增强算法具有各自的局限性,处理后的视觉效果并不理想。为了改善红外图像的视觉效果,增强图像中目标的识别力,研究了基于人眼视觉特性的Retinex算法,结合红外图像的成像机制,将适用于可见光图像的Retinex增强算法应用于红外图像,取得了良好的视觉效果。在此基础上,对算法进行自适应改进,提出了AMSR算法。采用几种传统的图像增强算法和基于Retinex的算法对具有典型特性的红外图像进行增强处理,并计算客观评价指标。通过对实验结果的主观评价和客观指标分析,验证了AMSR增强算法对红外图像具有适用性和优越性。本文的研究工作对红外目标探测和识别具有重要的意义。Infrared images have the characteristics of low contrast, big noise, wide dynamic range and poor visual effect, etc. In order to obtain a good visual effect and improve the target detection and recognition capabilities, Retinex enhancement algorithm based on human vision was studied. Combined with imaging mechanism of infrared image, Retinex method that is suitable for the visible light image is used for infrared image enhancement,and the ideal visual effect has been gotten through this method. On this basis, an adaptive multi -scale Retinex （AMSR） method is proposed. The infrared images is enhanced by this algorithm and the objective evaluation factors are calculated, and its enhancement effect compares with those of several traditional image enhancement algorithms. The experimental results show that the AMSR algorithm has the applicability and superiority for infrared images. This study is significant to the infrared target detection and recognition.

关 键 词：红外图像增强 RETINEX 图像客观评价指标 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]