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红外图像增强技术在TMS320DM642上的应用
引用本文:黄德天,吴志勇. 红外图像增强技术在TMS320DM642上的应用[J]. 红外, 2012, 33(4): 14-19
作者姓名:黄德天  吴志勇
作者单位:中国科学院长春光学精密机械与物理研究所,中国科学院长春光学精密机械与物理研究所
基金项目:国家863高技术研究发展计划资助项目(No.2008AA7034320B)
摘    要:针对红外图像普遍存在目标与背景对比度差、边缘模糊、信噪比低和灰度层次差等缺陷,提出了一种改进的直方图均衡红外图像增强算法。首先通过自适应地选择合适的灰度阈值,在图像直方图中将像素所占比例小于阈值的冗余灰度级完全压缩,并对大于阈值的有效灰度级进行基于一种非常合理的对数函数的拉伸变换;然后对拉伸后的灰度级进行常规的直方图均衡处理;最后在整个灰度范围内对经过均衡处理的图像灰度级进行等间距排列。为了满足算法的实时性,设计了一种以TMS320DM642高性能DSP芯片为核心处理器的红外图像增强系统平台。实验结果表明,采用该算法增强后的图像质量明显优于采用直方图均衡算法增强后的图像质量,图像的目标与背景的对比度和图像的清晰度都得到了提高,边缘细节也得到了保留;同时,采用该算法处理一帧320×256×8bits的红外图像仅仅用时16.73ms,完全满足实时图像处理的要求。

关 键 词:红外图像  直方图均衡  实时图像处理  TMS320DM642
收稿时间:2012-02-27
修稿时间:2012-03-05

Application of Infrared Image Enhancement Technology to TMS320DM642
HUANG DE TIAN and WU ZHI YONG. Application of Infrared Image Enhancement Technology to TMS320DM642[J]. Infrared, 2012, 33(4): 14-19
Authors:HUANG DE TIAN and WU ZHI YONG
Affiliation:Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences,Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences
Abstract:Because infrared images usually have the disadvantages of low contrast, blurry edge, low signal-to-noise ratio (SNR) and less gray levels, an improved infrared image enhancement algorithm based on histogram equalization is proposed. Firstly, by adaptively selecting an proper threshold, the redundant gray levels which have pixel sum less than the threshold are completely compressed and those effective gray levels which have pixel sum greater than the threshold are stretched on the basis of a very rational logarithm transformation. Secondly, a conventional histogram equalization method is used to process the stretched gray levels. Finally, all these equalized gray levels are arranged at an equal distance in the whole gray level area. To meet the real-time requirement, an infrared image enhancement system which uses a TMS320DM642 chip as its core processor is designed. The experimental result shows that the image enhanced by using this algorithm is obviously better than the one enhanced by using the conventional histogram equalization algorithm in quality. The object-background contrast and definition of the image are both improved and the edge details are kept. Moreover, it takes only 16.73 ms for the algorithm to process an image with $320times256times8$ bits. So, the requirement of real-time image processing can be satisfied completely.
Keywords:infrared image   histogram equalization   real-time image processing   TMS320DM642
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