基于MSR和AMSR的红外融合增强算法

doi:10.3969/j.issn.0255-8297.2022.03.006

摘要/Abstract

摘要： 红外传感器的成像特点，使得所采集的红外图像存在对比度低、清晰度差、信噪比低、边缘信息模糊等问题。为此提出基于多尺度视网膜（multi-scale retinex,MSR）和自适应多尺度视网膜（adaptive multi-scale retinex,AMSR）的红外融合增强及其优化算法。实验结果表明，所提算法能够有效提高红外图像的对比度和清晰度，在主观视觉效果和客观评价指标上均优于单尺度视网膜算法、MSR算法、AMSR算法。

关键词: 红外, 融合增强, 多尺度视网膜, 自适应多尺度视网膜

Abstract: There are some problems related to infrared images, such as low contrast, poor definition, low signal to noise ratio and blurred edge information for infrared sensors. In this paper, an infrared fusion enhancement algorithm and the improvement of the algorithm are proposed based on the combination of multi-scale retinex (MSR) and adaptive multi-scale retinex (AMSR). Experimental results show that the proposed algorithms can improve the contrast and definition of infrared images. And the algorithms are better than single scale retinex (SSR), multi-scale retinex (MSR), adaptive multi-scale retinex (AMSR) in subjective visual effects and objective evaluation criteria.

Key words: infrared, fusion enhancement, multi-scale retinex (MSR), adaptive multi-scale retinex (AMSR)

中图分类号:

TP391.4

刘硕, 瞿崇晓, 祝中科, 张福俊, 范长军. 基于MSR和AMSR的红外融合增强算法[J]. 应用科学学报, 2022, 40(3): 423-433.

LIU Shuo, QU Chongxiao, ZHU Zhongke, ZHANG Fujun, FAN Changjun. Infrared Image Fusion Enhancement Algorithm Based on MSR and AMSR[J]. Journal of Applied Sciences, 2022, 40(3): 423-433.

参考文献

[1] 张承泓,李范鸣,吴滢跃.基于自适应引导滤波的子带分解多尺度retinex红外图像增强[J].红外技术, 2019, 41(4):323-328. Zhang C H, Li F M, Wu Y Y. Infrared image enhancement based on adaptive guided filter and sub-band decomposed multi-scale retinex[J]. Infrared Technology, 2019, 41(4):323-328.(in Chinese)
[2] Sadeghi M, Jones S B, Philpot W D. A linear physically-based model for remote sensing of soil moisture using short wave infrared bands[J]. Remote Sensing of Environment, 2015, 164:66-76.
[3] 袁小燕,张照锋,张登银,等.基于融合技术的单幅红外图像增强方法[J].电子器件, 2018, 41(4):976-985. Yuan X Y, Zhang Z F, Zhang D Y, et al. A fusion-based single infrared image enhancement method[J]. Chinese Journal of Electron Devices, 2018, 41(4):976-985.(in Chinese)
[4] 葛朋,杨波,韩庆林,等.一种基于引导滤波图像分层的红外图像细节增强算法[J].红外技术, 2018, 40(12):1161-1169. Ge P, Yang B, Han Q L, et al. Infrared image detail enhancement algorithm based on hierarchical processing by guided image filter[J]. Infrared Technology, 2018, 40(12):1161-1169.(in Chinese)
[5] 张云峰.基于场景复杂度计算的红外图像平台直方图均衡[J].液晶与显示, 2016, 31(7):695-702. Zhang Y F. Adaptive plateau histogram equalization for infrared image based on scene complexity computation[J]. Chinese Journal of Liquid Crystals and Displays, 2016, 31(7):695-702.(in Chinese)
[6] 靳阳阳,韩现伟,周书宁,等.图像增强算法综述[J].计算机系统应用, 2021, 30(6):18-27. Jin Y Y, Han X W, Zhou S N, et al. Review on image enhancement algorithms[J]. Computer Systems&Applications, 2021, 30(6):18-27.(in Chinese)
[7] 董丽丽,丁畅,许文海,等.基于直方图均衡化图像增强的两种改进方法[J].电子学报, 2018, 46(10):2367-2375. Dong L L, Ding C, Xu W H, et al. Two improved methods based on histogram equalization for image enhancement[J]. Acta Electronica Sinica, 2018, 46(10):2367-2375.(in Chinese)
[8] 郝宇,王新赛,张彦波,等.基于自适应尺度因子的retinex红外图像增强算法[J].红外技术, 2016, 38(10):855-859. Hao Y, Wang X S, Zhang Y B, et al. The infrared image enhancement algorithm based on adapted scale factor retinex[J]. Infrared Technology, 2016, 38(10):855-859.(in Chinese)
[9] 李毅,张云峰,张强,等.基于去雾模型的红外图像对比度增强[J].中国激光, 2015, 42(1):298-306. Li Y, Zhang Y F, Zhang Q, et al. Infrared image contrast enhancement based on haze remove method[J]. Chinese Journal of Lasers, 2015, 42(1):298-306.(in Chinese)
[10] 王晨,汤心溢,高思莉,等.基于人眼视觉的红外图像增强算法研究[J].激光与红外, 2017, 47(1):114-118. Wang C, Tang X Y, Gao S L, et al. Infrared image enhancement algorithm based on human vision[J]. Laser&Infrared, 2017, 47(1):114-118.(in Chinese)
[11] 谢昊伶,彭国华,王凡,等.基于背景光估计与暗通道先验的水下图像复原[J].光学学报, 2018, 38(1):10-19. Xie H L, Peng G H, Wang F, et al. Under-water image restoration based on background light estimation and dark channel prior[J]. Acta Optica Sinica, 2018, 38(1):10-19.(in Chinese)
[12] 刘洋,余建华,顾志芹,等.一种改进型增强图像处理算法研究与应用[J].激光与红外, 2019, 49(3):381-384. Liu Y, Yu J H, Gu Z Q, et al. Research and application of an improved enhanced image processing algorithm[J]. Laser&Infrared, 2019, 49(3):381-384.(in Chinese)
[13] 陈豪,赖惠成,高古学,等.基于多曝光图像融合的沙尘图像增强[J].光子学报, 2021, 50(9):300-312. Chen H, Lai H C, Gao G X, et al. Sand-dust image enhancement based on multi-exposure image fusion[J]. Acta Photonica Sinica, 2021, 50(9):300-312.(in Chinese)
[14] 臧维明,邓文,李红,等.基于异源图像引导的红外图像增强算法[J].中国电子科学研究院学报, 2017, 12(4):346-352. Zang W M, Deng W, Li H, et al. Infrared image enhancement algorithm based on multisensor images[J]. Journal of China Academy of Electronics and Information Technology, 2017, 12(4):346-352.(in Chinese)
[15] 陈志斌,张超,宋岩,等.灰度拉伸retinex在大动态范围烟雾图像增强中的应用[J].红外与激光工程, 2014, 43(9):3146-3150. Chen Z B, Zhang C, Song Y, et al. Application of retinex with grayscale stretching in large dynamic range smoke image enhancement[J]. Infrared and Laser Engineering, 2014, 43(9):3146-3150.(in Chinese)