Multispectral image enhancement based on illuminance-reflection imaging model and morphology operation

Wang Dian-Wei<sup>1\2</sup>; Han Peng-Fei; Fan Jiu-Lun; Liu Ying<sup>1\2</sup>; Xu Zhi-Jie; Wang Jing

doi:10.7498/aps.67.20181288

Abstract

In this paper we propose a multispectral image enhancement algorithm based on illuminance-reflection imaging model and morphology operation that enables us to solve the problem of improving the multispectral degraded images. Firstly, we transform the image from RGB space to HSV color space, and the hue remains unchanged. As for the saturation component, we use the adaptive nonlinear stretching to improve the image color saturation and brightness. Secondly, according to the illuminance-reflection imaging model, we adopt the guided image filtering method to decompose the brightness into illuminance component and reflection component. Usually, the illumination component mainly determines the dynamic range of the pixels in the image, corresponding to the low frequency part of the image, reflecting the global characteristics of the image and the edge detail information of the image; the reflected component represents the intrinsic essential characteristics of the image, corresponding to the high frequency part of the image, and contains most of the local detail information of the image as well as all noise. Thirdly, we present an improved adaptive gamma function, which can dynamically adjust the illuminance component by the local distribution characteristics, and use the contrast-limited adaptive histogram equalization to correct the illuminance component. Afterwards we propose a detail-feature weighted fusion strategy. The original illumination and the two corrected illuminations are fused to obtain the final illumination component. Fourthly, we propose an improved morphological operation to denoise and enhance the details of the reflection component. Finally, the corrected illumination component and the enhanced reflection component are combined to obtain the improved brightness component. In order to verify the efficiency of the algorithm proposed in the paper, we use both subjective visual effectiveness method and quantitative parameter analysis method to measure the enhancement performance in multispectral imaging scenarios, including low illumination image, underwater image, high-dynamic range image, sandstorm image, haze image and thermal infrared image. Then standard deviation, information entropy and average gradient are used as evaluation indices respectively, and qualitative and quantitative comparison with a variety of image enhancement algorithms show that the proposed algorithm can not only well suppress noise but also obviously improve local details and global contrast. Experimental results show that the proposed method proves to be better in performance.

Keywords:

Authors and contacts

1.
School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China;
2.
Key laboratory of Electronic Information Application Technology for Scene Investigation, Ministry of Republic Security, Xi'an 710121, China;
3.
School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK;
4.
Department of Computing, Sheffield Hallam University, Sheffield S1 1WB, UK

Corresponding author: Han Peng-Fei, 13772405149@126.com

Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61671377), the 2018 "Dual-Tutor System" Project for Innovation and Entrepreneurship of Natural Science Research Program of Shaanxi Province, China (Grant No. 2018JM6118), the Innovation and Entrepreneurship Project of Xi'an University of Posts and Telecommunications, China (Grant No. 2018SC-08), and the Xi'an University of Posts and Telecommunications Graduate Innovation Fund, China (Grant No. CXJJ2017057).

References

[1]	Chen X H, Yan L, Wu W, Meng S Y, Wu L A, Sun Z B, Wang C, Zhai G J 2017 Chin. Phys. B 26 60702
[2]	Lu X W, Li J Z, Chen H Y 2010 Chin. Phys. Lett. 27 104209
[3]	Bi G L, Xu Z J, Zhao J, Sun Q 2015 Acta Phys. Sin. 64 100701 (in Chinese)[毕国玲, 续志军, 赵健, 孙强 2015 物理学报 64 100701]
[4]	Li H, Wu W, Yang X M, Yan B Y, Liu K, Jeon G 2016 Acta Phys. Sin. 65 160701 (in Chinese)[李红, 吴炜, 杨晓敏, 严斌宇, 刘凯, Gwanggil Jeon 2016 物理学报 65 160701]
[5]	Sim K S, Tso C P, Tan Y Y 2007 Pattern Recogn. Lett. 28 1209
[6]	Sasi N M, Jayasree V K 2013 Engineering 5 326
[7]	Chen Q, Bai L H, Zhang B M 2003 J. Infrared Millim. Waves 22 428 (in Chinese)[陈钱, 柏连发, 张保民 2003 红外与毫米波学报 22 428]
[8]	Jobson D J, Rahman Z, Woodell G A 1997 IEEE Trans. Image Process. 6 451
[9]	Rahman Z, Jobson D J, Woodell G A 2002 International Conference on Image Processing Lausanne, Switzerland, September 19, 1996 p1003
[10]	Jobson D J, Rahman Z, Woodell G A 1997 IEEE Trans. Image Process. 6 965
[11]	Fu X, Zhuang P, Huang Y, Liao Y, Zhang X P, Ding X 2015 IEEE International Conference on Image Processing Quebec City, Canada, Septmber 27-30, 2014 p4572
[12]	He K, Sun J, Tang X 2013 IEEE Trans. Pattern Anal. 35 1397
[13]	Li Z, Zheng J, Zhu Z, Yao W, Wu S 2015 IEEE Trans. Image Process. 24 120
[14]	Li H P 2014 M. S. Thesis (Kunming: Yunnan University) (in Chinese)[李红平2014 硕士学位论文 (昆明: 云南大学)]
[15]	Durand F, Dorsey J 2002 Acm Trans. Graphic 21 257
[16]	He K, Sun J, Tang X 2011 IEEE Trans. Pattern Anal. 33 2341
[17]	Li H Y, Zhong M Z 2016 J. Kashgar Univ. 37 42 (in Chinese)[李海燕, 钟梦之 2016 喀什大学学报 37 42]
[18]	Fu X, Zeng D, Huang Y, Ding X, Zhang X P 2014 IEEE Global Conference on Signal and Information Processing Austin, TX, USA, December 3-5, 2013 p1085
[19]	Song R X, Li D, Wang X C 2017 J. Graphics 38 217 (in Chinese)[宋瑞霞, 李达, 王小春 2017 图学学报 38 217]
[20]	Ying Z, Li G, RenY, Wang R, Wang W 2017 Computer Analysis of Images and Patterns 17th International Conference Proceedings, Part II Ystad, Sweden, August 22-24, 2017 p36
[21]	Li M, Liu J, Yang W, Sun X, Guo Z 2018 IEEE Trans. Image Process. 27 2828
[22]	Ying Z, Li G, Ren Y, Wang R, Wang W 2017 IEEE International Conference on Computer Vision Workshop, IEEE Computer Society Venice, Italy, October 22-29, 2017 p3015
[23]	Fu X, Liao Y, Zeng D, Huang Y, Zhang X P, Ding X 2015 IEEE Trans. Image Process. 24 4965
[24]	Guo X, Li Y, Ling H 2017 IEEE Trans. Image Process. 26 982
[25]	Fu X, Zeng D, Huang Y, Liao Y, Ding X, Paisley J 2016 Signal Process. 129 82
[26]	Lu B P, Li Y J, Zheng Y M, Wang Y K 2017 J. Chin. Mini-Micro Comput. Syst. 38 625 (in Chinese) [芦碧波, 李玉静, 郑艳梅, 王玉琨 2017 小型微型计算机系统 38 625]
[27]	Reinhard E, Stark M, Shirley P, Ferwerda J 2002 Conference on Computer Graphics & Interactive Techniques San Antonio, Texas, USA, July 21-26, 2002 p267
[28]	Cai B, Xu X, Jia K, Qing C, Tao D 2016 IEEE Trans. Image Process. 25 5187
[29]	Berman D, Treibitz T, Avidan S 2016 IEEE Conference on Computer Vision and Pattern Recognition Las Vegas, NV, USA, June 27-30, 2016 p1674
[30]	Fu X, Huang Y, Zeng D, Zhang X P, Ding X 2014 IEEE International Workshop on Multimedia Signal Processing Jakarta, Indonesia, September 22-24, 2014 p1
[31]	Li W, Yi B, Huang T, Yao W, Peng H 2016 KSⅡ Trans. Internet Inf. 10 1846
[32]	Lee S 2007 IEEE Trans. Circ. Syst. Vid. 17 199
[33]	Chen X H, Wu W, Meng S Y, Li M Y 2014 Chin. Phys. B 23 90701
[34]	Ji D J, Qu G R, Hu C H, Liu B D, Jian J B, Guo X K 2017 Chin. Phys. B 26 60701

Cited By

[1]	Chen X H, Yan L, Wu W, Meng S Y, Wu L A, Sun Z B, Wang C, Zhai G J 2017 Chin. Phys. B 26 60702
[2]	Lu X W, Li J Z, Chen H Y 2010 Chin. Phys. Lett. 27 104209
[3]	Bi G L, Xu Z J, Zhao J, Sun Q 2015 Acta Phys. Sin. 64 100701 (in Chinese)[毕国玲, 续志军, 赵健, 孙强 2015 物理学报 64 100701]
[4]	Li H, Wu W, Yang X M, Yan B Y, Liu K, Jeon G 2016 Acta Phys. Sin. 65 160701 (in Chinese)[李红, 吴炜, 杨晓敏, 严斌宇, 刘凯, Gwanggil Jeon 2016 物理学报 65 160701]
[5]	Sim K S, Tso C P, Tan Y Y 2007 Pattern Recogn. Lett. 28 1209
[6]	Sasi N M, Jayasree V K 2013 Engineering 5 326
[7]	Chen Q, Bai L H, Zhang B M 2003 J. Infrared Millim. Waves 22 428 (in Chinese)[陈钱, 柏连发, 张保民 2003 红外与毫米波学报 22 428]
[8]	Jobson D J, Rahman Z, Woodell G A 1997 IEEE Trans. Image Process. 6 451
[9]	Rahman Z, Jobson D J, Woodell G A 2002 International Conference on Image Processing Lausanne, Switzerland, September 19, 1996 p1003
[10]	Jobson D J, Rahman Z, Woodell G A 1997 IEEE Trans. Image Process. 6 965
[11]	Fu X, Zhuang P, Huang Y, Liao Y, Zhang X P, Ding X 2015 IEEE International Conference on Image Processing Quebec City, Canada, Septmber 27-30, 2014 p4572
[12]	He K, Sun J, Tang X 2013 IEEE Trans. Pattern Anal. 35 1397
[13]	Li Z, Zheng J, Zhu Z, Yao W, Wu S 2015 IEEE Trans. Image Process. 24 120
[14]	Li H P 2014 M. S. Thesis (Kunming: Yunnan University) (in Chinese)[李红平2014 硕士学位论文 (昆明: 云南大学)]
[15]	Durand F, Dorsey J 2002 Acm Trans. Graphic 21 257
[16]	He K, Sun J, Tang X 2011 IEEE Trans. Pattern Anal. 33 2341
[17]	Li H Y, Zhong M Z 2016 J. Kashgar Univ. 37 42 (in Chinese)[李海燕, 钟梦之 2016 喀什大学学报 37 42]
[18]	Fu X, Zeng D, Huang Y, Ding X, Zhang X P 2014 IEEE Global Conference on Signal and Information Processing Austin, TX, USA, December 3-5, 2013 p1085
[19]	Song R X, Li D, Wang X C 2017 J. Graphics 38 217 (in Chinese)[宋瑞霞, 李达, 王小春 2017 图学学报 38 217]
[20]	Ying Z, Li G, RenY, Wang R, Wang W 2017 Computer Analysis of Images and Patterns 17th International Conference Proceedings, Part II Ystad, Sweden, August 22-24, 2017 p36
[21]	Li M, Liu J, Yang W, Sun X, Guo Z 2018 IEEE Trans. Image Process. 27 2828
[22]	Ying Z, Li G, Ren Y, Wang R, Wang W 2017 IEEE International Conference on Computer Vision Workshop, IEEE Computer Society Venice, Italy, October 22-29, 2017 p3015
[23]	Fu X, Liao Y, Zeng D, Huang Y, Zhang X P, Ding X 2015 IEEE Trans. Image Process. 24 4965
[24]	Guo X, Li Y, Ling H 2017 IEEE Trans. Image Process. 26 982
[25]	Fu X, Zeng D, Huang Y, Liao Y, Ding X, Paisley J 2016 Signal Process. 129 82
[26]	Lu B P, Li Y J, Zheng Y M, Wang Y K 2017 J. Chin. Mini-Micro Comput. Syst. 38 625 (in Chinese) [芦碧波, 李玉静, 郑艳梅, 王玉琨 2017 小型微型计算机系统 38 625]
[27]	Reinhard E, Stark M, Shirley P, Ferwerda J 2002 Conference on Computer Graphics & Interactive Techniques San Antonio, Texas, USA, July 21-26, 2002 p267
[28]	Cai B, Xu X, Jia K, Qing C, Tao D 2016 IEEE Trans. Image Process. 25 5187
[29]	Berman D, Treibitz T, Avidan S 2016 IEEE Conference on Computer Vision and Pattern Recognition Las Vegas, NV, USA, June 27-30, 2016 p1674
[30]	Fu X, Huang Y, Zeng D, Zhang X P, Ding X 2014 IEEE International Workshop on Multimedia Signal Processing Jakarta, Indonesia, September 22-24, 2014 p1
[31]	Li W, Yi B, Huang T, Yao W, Peng H 2016 KSⅡ Trans. Internet Inf. 10 1846
[32]	Lee S 2007 IEEE Trans. Circ. Syst. Vid. 17 199
[33]	Chen X H, Wu W, Meng S Y, Li M Y 2014 Chin. Phys. B 23 90701
[34]	Ji D J, Qu G R, Hu C H, Liu B D, Jian J B, Guo X K 2017 Chin. Phys. B 26 60701

[1]	Zhang Yin-Sheng, Tong Jun-Yi, Chen Ge, Shan Meng-Jiao, Wang Shuo-Yang, Shan Hui-Lin. Synthetic aperture optical image restoration based on multi-scale feature enhancement. Acta Physica Sinica, 2024, 73(6): 064203. doi: 10.7498/aps.73.20231761
[2]	Jiang Bi-Yi, Zhou Fei-Chi, Chai Yang. Application of neuromorphic resistive random access memory in image processing. Acta Physica Sinica, 2022, 71(14): 148504. doi: 10.7498/aps.71.20220463
[3]	Wu Xiao-Wa, Qin Si-Qing, Xue Lei, Yang Bai-Cun, Zhang Ke. Behavior characteristics from self-organization to criticality caused by cumulative damage leading to instability of locked segments in seismogenic fault system. Acta Physica Sinica, 2018, 67(20): 206401. doi: 10.7498/aps.67.20180614
[4]	Cai Qi-Sheng, Huang Min, Han Wei, Liu Yi-Xuan, Lu Xiang-Ning. Simulation of multiband imaging technology of large aperture spatial heterodyne imaging spectroscopy. Acta Physica Sinica, 2018, 67(23): 234205. doi: 10.7498/aps.67.20180943
[5]	Liu Jie, Zhang Jian-Xun, Dai Yu. Image enhancement based on multi-guided filtering. Acta Physica Sinica, 2018, 67(23): 238701. doi: 10.7498/aps.67.20181425
[6]	Li Hong, Wu Wei, Yang Xiao-Min, Yan Bin-Yu, Liu Kai, Gwanggil Jeon. Multispectral image enhancement based on Retinex by using structure extraction. Acta Physica Sinica, 2016, 65(16): 160701. doi: 10.7498/aps.65.160701
[7]	Yi Shi-He, Chen Zhi. Review of recent experimental studies of the shock train flow field in the isolator. Acta Physica Sinica, 2015, 64(19): 199401. doi: 10.7498/aps.64.199401
[8]	Zhao Liao-Ying, Lü Bu-Yun, Li Xiao-Run, Chen Shu-Han. Multi-source remote sensing image registration based on scale-invariant feature transform and optimization of regional mutual information. Acta Physica Sinica, 2015, 64(12): 124204. doi: 10.7498/aps.64.124204
[9]	Li Xin-Nan, Huang He-Yan, Jia Xiao-Ning, Ma Si-Liang. Guided filter-based blind image restoration method. Acta Physica Sinica, 2015, 64(13): 134202. doi: 10.7498/aps.64.134202
[10]	Bi Guo-Ling, Xu Zhi-Jun, Zhao Jian, Sun Qiang. Multispectral image enhancement based on irradiation-reflection model and bounded operation. Acta Physica Sinica, 2015, 64(10): 100701. doi: 10.7498/aps.64.100701
[11]	Pang Yu, Deng Lu, Lin Jin-Zhao, Li Zhang-Yong, Zhou Qian-Neng, Li Guo-Quan, Huang Hua-Wei, Zhang Yi, Wu Wei. A method of removing baseline drift in ECG signal based on morphological filtering. Acta Physica Sinica, 2014, 63(9): 098701. doi: 10.7498/aps.63.098701
[12]	Wen Qiao, Wang Kai-Ge, Shao Yong-Hong, Qu Jun-Le, Niu Han-Ben. A nnovel wide field fluorescence sectioning microscope based on polarization filtering image enhancement and dynamic speckle illumination. Acta Physica Sinica, 2013, 62(3): 034203. doi: 10.7498/aps.62.034203
[13]	Qin Xiu-Juan, Shao Guang-Jie, Liu Ri-Ping, Wang Wen-Kui, Yao Yu-Shu, Meng Hui-Min. Preparation and Raman spectra of high quality ZnO nano-bulk materials. Acta Physica Sinica, 2006, 55(7): 3760-3765. doi: 10.7498/aps.55.3760
[14]	Luo Lin, Wang Li, Cheng Wei-Dong, Shen Mang-Zuo. Approaches to convergence enhancement of multiframe blind deconvolution of astronomical images. Acta Physica Sinica, 2006, 55(12): 6708-6714. doi: 10.7498/aps.55.6708
[15]	Wang Yi, Zhai Hong-Chen, Mu Guo-Guang. Fuzzy matching of images based on shape description matrix. Acta Physica Sinica, 2005, 54(5): 1965-1968. doi: 10.7498/aps.54.1965
[16]	Liu Hai-Wen, Sun Xiao-Wei, Li Zheng-Fan, Qian Rong, Zhou Min. A low-pass filter of wide stopband with a novel dual-layer fractal photonic band gap structure. Acta Physica Sinica, 2003, 52(12): 3082-3086. doi: 10.7498/aps.52.3082
[17]	Min Fu-Hong, Xu Wen-Bo, Xu Zhen-Yuan. . Acta Physica Sinica, 2002, 51(8): 1690-1695. doi: 10.7498/aps.51.1690
[18]	LI LIU-HE, ZHANG HAI-QUAN, CUI XU-MING, ZHANG YAN-HUA, XIA LI-FANG, MA XIN-XIN, SUN YUE. COMPARATIVE ANALYSIS OF DLC FLIM FINE STRUCTURE BY RAMAN SPECTRA AND X-RAY PHOTOELECTRON SPECTROSCOPY. Acta Physica Sinica, 2001, 50(8): 1549-1554. doi: 10.7498/aps.50.1549
[19]	CAI CHAO-HONG, XU ZHEN-YUAN, XU WEN-BO. DIRECT CHAOS TOWARDS LOW PERIOD MOTION BASED ON NOTCH FILTER FEEDBACK CONTROL. Acta Physica Sinica, 2001, 50(10): 1846-1850. doi: 10.7498/aps.50.1846
[20]	GU BEN-YUAN, DONG BI-ZHEN, ZHENG SHI-HAI, YANG GUO-ZHEN. SPACE-INVARIANT AND ROTATION-INVARIANT IN A GIVEN ANGLE RANGE PATTERN RECOGNITION AND THEIR FILTER DESIGN. Acta Physica Sinica, 1985, 34(6): 760-765. doi: 10.7498/aps.34.760

Catalog

Vol. 67, Issue 21 - 2018-11-05

Metrics

Abstract views: 7780
PDF Downloads: 168
Cited By: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

Search

Article

留言板