[1]李牧,周瑞杰,田哲嘉.基于直方图的热红外图像增强方[J].红外技术,2020,42(9):880-885.[doi:10.11846/j.issn.1001_8891.202009010]
 LI Mu,ZHOU Ruijie,TIAN Zhejia.A Thermal Infrared Image Enhancement Method Based on Histogram[J].Infrared Technology,2020,42(9):880-885.[doi:10.11846/j.issn.1001_8891.202009010]
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基于直方图的热红外图像增强方
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《红外技术》[ISSN:1001-8891/CN:CN 53-1053/TN]

卷:
42卷
期数:
2020年第9期
页码:
880-885
栏目:
出版日期:
2020-09-23

文章信息/Info

Title:
A Thermal Infrared Image Enhancement Method Based on Histogram
文章编号:
1001-8891(2020)09-0880-06
作者:
李牧周瑞杰田哲嘉
西安理工大学 自动化与信息工程学院
Author(s):
LI MuZHOU RuijieTIAN Zhejia
School of Automation and Information Engineering, Xi’an University of Technology
关键词:
热红外图像图像增强直方图均衡化直方图裁剪
Keywords:
image enhancementhistogram equalizationthermal infrared imagehistogram clipping
分类号:
TP391
DOI:
10.11846/j.issn.1001_8891.202009010
文献标志码:
A
摘要:
为了改善热红外图像的增强效果,本文提出了一种基于改进的直方图裁剪方法的热红外图像增强算法。该算法核心是确定热红外原始图像与传统的直方图均衡化图像的直方图bins中像素点的数量差,再根据范围准则,将计算出的不同bins的差值划分为不同的区块。然后重新分配直方图,确定变换函数,得到增强后的热红外图像。该算法是一种改进的全局直方图均衡化方法,在对比度增强、直方图形状和细节信息之间可以做到较好的平衡。本文算法的峰值信噪比、结构相似度和均方误差的平均值分别为27.5、0.923和0.59,均优于其他算法,实验结果表明,该方法能有效增强热红外图像。
Abstract:
?To improve the enhancement of infrared thermal images, this paper proposes an algorithm based on an improved histogram clipping method. The algorithm determines the difference between the number of pixels in the histogram bins of the original thermal infrared image and the traditional histogram equalization image. Subsequently, based on a specific range criterion, the calculated difference of various histogram bins is divided into different blocks. Next, the histogram is redistributed, and a transform function is determined to obtain the enhanced thermal infrared image. The algorithm is based on an improved global histogram equalization method, which achieves a suitable balance between contrast enhancement, histogram shape, and detail information. The experimental results demonstrate that the average values of the peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and mean-square error (MSE)—27.5, 0.923, and 590 respectively are better than those of other algorithms. Thus, this method effectively enhances the thermal infrared image.

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备注/Memo

备注/Memo:
收稿日期:2020-01-08;修订日期:2020-08-22.
作者简介:李牧(1973-),男,高级工程师,研究方向为基于热红外的物体特征提取技术研究。
通信作者:周瑞杰(1995-),男,硕士研究生,研究方向为雷达、热红外信息融合。E-mail:2170321217@stu.xaut.edu.cn。

更新日期/Last Update: 2020-09-21