-
摘要:图像增强算法能够提高图像整体和局部的对比度，突出图像的细节信息，使增强后的图像更符合人眼的视觉特性且易于机器识别，在军事和民用领域具有广泛的应用。本文从图像增强算法的原理出发，归纳总结了近年来应用比较广泛的4类图像增强算法及其改进算法，包括直方图均衡图像增强算法、小波变换图像增强算法、偏微分方程图像增强算法和基于Retinex理论的图像增强算法。结合人眼视觉特性、噪声抑制、亮度保持和信息熵最大化等图像增强的改进算法，在保证增强图像具有较高对比度的前提下，可进一步提升图像的质量。实现了9种较为典型的图像增强算法，采用主观和客观的评价方法对增强效果进行了对比，分析了不同增强算法的优缺点，并给出了这些算法的计算时间。对这些算法的深入研究能够推动图像增强技术向更高水平发展，从而使图像增强技术在多个学科领域发挥重要作用。Abstract:Image enhancement algorithms can enhance contrast between the whole and partial images, and highlight the details of images. It also can make the enhanced images more in line with the visual characteristics of the human eyes and it applies to machine identification, which has a wide range of applications in military and civilian fields. Based on the principle of image enhancement algorithm, four types of image enhancement algorithms and their improved algorithms are summarized in this paper. These algorithms include histogram equalization image enhancement algorithm, wavelet transform image enhancement algorithm, partial differential equation image enhancement algorithm and Retinex image enhancement algotithm. These improved algorithms, which combine the human visual characteristics, noise suppression, brightness preserving and information entropy maximization, can further improve the quality of images in addition to enhancing the contrast. In this paper, nine typical image enhancement algorithms are implemented, and their enhancement effects are compared with subjective and objective evaluation methods. The advantages and disadvantages of these enhancement algorithms are analyzed, and the calculation time of the algorithms are given. The study on these algorithms can promote the image enhancement technology to a higher level, so as to make the image enhancement technology play an important role in many fields.
-
图 1不同算法得到的增强图像及其对应的直方图(1)
Figure 1.Enhanced images obtained by different algorithms and their corresponding histograms (1)
图 2不同算法得到的增强图像及其直方图(2)
Figure 2.Enhanced images obtained by different algorithms and their corresponding histograms (2)
表 1不同算法得到的图像质量的客观评价结果
Table 1.Objective evaluation results of images quality obtained by different algorithms
Evaluation
resultOriginal HE BBHE LMHE WT KGWT PDE TVPDE SSR MSR 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 Contrast 8.7 18.3 31.7 24.9 25.3 26.8 28.5 30.5 29.0 33.9 24.9 36.1 33.5 42.3 38.1 28.4 23.7 38.0 27.4 30.6 Signal to
noise ratio7.5 9.4 10.3 12.5 9.7 14.1 13.9 13.6 11.4 10.3 12.4 13.9 23.0 13.7 28.3 16.3 30.6 21.5 32.9 24.9 Information
entropy1.6 3.0 3.7 3.4 3.4 3.7 3.9 4.0 3.8 4.3 3.6 4.6 4.2 4.7 4.1 4.5 4.8 5.1 5.1 5.0 
下载:
导出CSV
表 2不同算法的计算时间(ms)
Table 2.Computation time of different algorithms (ms)
Resolution/(pixel×pixel) HE BBHE LMHE WT KGWT PDE TVPDE SSR MSR 256×256 3 5 7 18 22 17 28 13 30 640×512 11 15 34 95 108 90 116 66 125 1024×1024 36 45 109 306 381 277 316 208 343 下载:
导出CSV
-
[1] 郝志成, 吴川, 杨航, 等.基于双边纹理滤波的图像细节增强方法[J].中国光学, 2016, 9(4):423-431.//www.illord.com/CN/abstract/abstract9409.shtmlHAO Z C, WU C, YANG H, et al.. Image detail enhancement method based on multi-scale bilateral texture filter[J]. Chinese Optics, 2016, 9(4):423-431. (in Chinese)//www.illord.com/CN/abstract/abstract9409.shtml [2] ZIMMERMAN J B, PIZER S M, STAAB E V, et al.. An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement[J]. IEEE Transactions on Medical Imaging, 1988, 7(4):304-312.doi:10.1109/42.14513 [3] WANG Q, WARD R K. Fast image/video contrast enhancement based on weighted thresholded histogram equalization[J]. IEEE Transactions on Consumer Electronics, 2007, 53(2):757-764.doi:10.1109/TCE.2007.381756 [4] YANG S, OH J H, PARK Y. Contrast enhancement using histogram equalization with bin underflow and bin overflow[C]. Proceedings of 2003 International Conference on Image Processing, Barcelona, Spain, 2003:881-884. [5] KIM Y T. Contrast enhancement using brightness preserving bi-histogram equalization[J]. IEEE, 1997, 43(1):1-8.https://www.researchgate.net/publication/278860756_Contrast_enhancement_using_brightness_preserving_bi-histogram_equalization [6] WAN Y, CHEN Q, ZHANG B M. Image enhancement based on equal area dualistic sub-image histogram equalization method[J]. IEEE, 1999, 45(1):68-75.https://www.researchgate.net/publication/3180079_Image_enhancement_based_on_equal_area_dualistic_sub-image_histogram_equalization_method [7] CHEN S, RAMLI A. Minimum mean brightness error bi-histogram equalization in contrast enhancement[J]. IEEE, 2003, 49(4):1310-1319.https://www.researchgate.net/profile/Soong_Der_Chen/publication/3180783_Minimum_mean_brightness_error_Bi-histogram_equalization_in_contrast_enhancement/links/02e7e51a660fbe25c0000000.pdf?inViewer=true&pdfJsDownload=true&disableCoverPage=true&origin=publication_detail [8] KIM W K, YOU J M, JEONG J. Contrast enhancement using histogram equalization based on logarithmic mapping[J]. Optical Engineering, 2012, 51(6):1-10.https://www.researchgate.net/publication/258687974_Contrast_enhancement_using_histogram_equalization_based_on_logarithmic_mapping [9] CELIK T. Spatial entropy-based global and local image contrast enhancement[J]. IEEE, 2014, 23(12):5298-5308.https://www.researchgate.net/publication/267743087_Spatial_Entropy-Based_Global_and_Local_Image_Contrast_Enhancement [10] 倪林.小波变换与图像处理[M].合肥:中国科学技术大学出版社, 2010.NI L. Wavelet Transform and Image Processing[M]. Hefei:University of Science and Technology of China Press, 2010. (in Chinese) [11] 丁西明. 基于小波变换的图像增强研究[D]. 安徽: 安徽大学, 2010.DING X M.The study of image enhancement algorithm based on wavelet transform[D]. Anhui:Anhui University, 2010. (in Chinese) [12] DEMIREL H, ANBARJAFARI G. Image resolution enhancement by using discrete and stationary wavelet decomposition[J]. IEEE, 2011, 20(5):1458-60.https://www.researchgate.net/publication/224183525_IMAGE_Resolution_Enhancement_by_Using_Discrete_and_Stationary_Wavelet_Decomposition [13] DEMIREL H, ANBARJAFARI G. Discrete wavelet transform based satellite image resolution enhancement[J]. IEEE, 2011, 49(6):1997-2004.http://oaji.net/articles/2015/1948-1436440743.pdf [14] LOZA A, BULL D R, HILL P R, et al.. Automatic contrast enhancement of low-light images based on local statistics of wavelet coefficients[J]. Digital Signal Process, 2013, 23(6):1856-1866.doi:10.1016/j.dsp.2013.06.002 [15] CHO D W, BUI T D. Fast image enhancement in compressed wavelet domain[J]. Signal Process, 2014, 98(1):295-307.https://www.researchgate.net/publication/221121835_Fast_image_enhancement_in_compressed_wavelet_domain [16] NASRI M, POUR H N. Image denoising in the wavelet domain using a new adaptive thresholding function[J]. Neurocomputing, 2009, 72(3):1012-1025.https://www.researchgate.net/publication/220549893_Image_denoising_in_the_wavelet_domain_using_a_new_adaptive_thresholding_function [17] CHANG S, YU B, VETTERLI M. Adaptive wavelet thresholding for image denoising and compression[J]. IEEE, 2000, 9(4):1532-1546.https://www.researchgate.net/publication/287609205_Adaptive_wavelet_thresholding_for_image_denoising_and_compression [18] BHANDARI A K, KUMAR A, SINGH G K. Improved knee transfer function and gamma correction based method for contrast and bringtness enhancement of satellite image[J]. Inernational Journal of Electronics and Communications, 2015, 69(1):579-589.http://www.sciencedirect.com/science/journal/14348411/69/2 [19] SE E K, JONG J J, IL K E. Image contrast enhancement using entropy scaling in wavelet domain[J]. Signal Processing, 2016, 127(1):1-11.https://www.researchgate.net/profile/Il_Eom/publication/296691441_Image_contrast_enhancement_using_entropy_scaling_in_wavelet_domain/links/57316fd708ae100ae5575548.pdf?origin=publication_list [20] DEMIREL H, OZCINAR C, ANBARJAFARI G. Satellite image contrast enhancement using discrete wavelet transform and singular value decomposition[J]. IEEE, 2010, 7(2):333-337.https://www.researchgate.net/publication/224083054_Satellite_Image_Contrast_Enhancement_Using_Discrete_Wavelet_Transform_and_Singular_Value_Decomposition [21] BHUTADA G G, ANAND R S, SAXENA S C. Edge preserved image enhancement using adaptive fusion of miages denoised by wavelet and cruvelet transform[J]. Digital Signal Processing, 2011, 21(1):118-130.doi:10.1016/j.dsp.2010.09.002 [22] BHAT P, ZITNICK C L, COHEN M, et al.. Gradient Shop:A gradient-domain optimization framework for image and video filtering[J]. ACM Transactions on Graphics, 2010, 29(2):1-14.http://grail.cs.washington.edu/projects/gradientshop/ [23] BHAT P, CURLESS B, COHEN M, et al. Fourier analysis of the 2D screened poisson equation for gradient domain problems[C]. The European Conference on Computer Vision, Marseille, France, 2008:114-128. [24] 孔平. 基于偏微分方程的图像去噪与增强研究[D]. 南京: 南京理工大学, 2012.KONG P. The study of image denoising and enhancement based on partial differential equation[D]. Nanjing:Nanjing University of Science and Technology, 2012. (in Chinese) [25] 王帅. 基于偏微分方程图像增强技术的研究[D]. 长春: 长春理工大学, 2012.WANG S. The study of image enhancement technology based on partial differential equation[D]. Changchun:Changchun University of Science and Technology, 2012. (in Chinese) [26] 王超. 基于变分问题和偏微分方程的图像处理技术研究[D]. 合肥: 中国科学技术大学, 2007.WANG C. Image processing based on variational problems and partial differential equations[D]. Hefei:University of Science and Technology of China, 2007. (in Chinese) [27] CHAN T F, SHEN J H. 图像处理与分析[M]. 陈文斌, 程晋, 译. 北京: 科学出版社, 2011.CHAN T, SHEN J H. Image processing and analysis[M]. Beijing:Science Press, 2011. (in Chinese) [28] KIM J H, KIM J H, JUNG S W, et al.. Novel contrast enhancement scheme for infrared image using detail-preserving stretching[J]. Optical Engineering, 2011, 50(7):1-10.http://opticalengineering.spiedigitallibrary.org/pdfaccess.ashx?url=/data/journals/optice/23432/077002_1.pdf [29] 韩希珍, 赵建.结合偏微分方程增强图像纹理及对比度[J].光学精密工程, 2012, 20(6):1382-1388.http://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201206032.htmHAN X Z, ZHAO J. Enhancement of image texture and contrast combined with partial differential equation[J]. Optics and Precision Engineering, 2011, 50(7):1-10. (in Chinese)http://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201206032.htm [30] LAND E. The Retinex[J]. America Science, 1964, 52(2):247-264.https://dragon.larc.nasa.gov/background/pubabs/papers/msrcrcmpr.pdf [31] LAND E, MCCANN J. Ligntness and Retinex theory[J]. Journal of the Optical Society of America, 1971, 61(1):1-11.doi:10.1364/JOSA.61.000001 [32] GONZALES A M, GRIGORYAN A M. Fast Retinex for color image enhancement:Methods and algorithms[J]. SPIE, 2015, 9411:1-12.http://proceedings.spiedigitallibrary.org/pdfaccess.ashx?url=/data/conferences/spiep/82998/94110f.pdf [33] SHEN C T, HWANG W L. Color image enhancement using Retinex with robust envelope[C]. 16th IEEE International Conference on Image Process, Cairo, Egypt, 2009:3141-3144. [34] WHARTON E, PANETTA K, AGAIAN S. Human visual system-based image enhancement and logarithmic contrast measure[J]. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 2008, 38(1):174-188.doi:10.1109/TSMCB.2007.909440 [35] JOBSON D, RAHMAN Z, WOODELL G. A multiscale Retinex for bridging the gap between color images and the human observation of scenes[J]. IEEE, 1997, 6(7):965-976.https://www.researchgate.net/publication/220503072_A_multiscale_retinex_for_bridging_the_gap_between_color_images_and_the_human_observation_of_scenes [36] 赵宏宇, 肖创柏, 禹晶, 等.马尔科夫随机场模型下的Retinex夜间彩色图像增强[J].光学精密工程, 2014, 22(4):1048-1055.http://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201404032.htmZHAO H Y, XIAO C B, YU J, et al.. A Retinex algorithm for night color image enhancement by MRF[J]. Optics and Precision Engineering, 2014, 22(4):1048-1055. (in Chinese)http://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201404032.htm [37] FU X Y, LIN Q, GUO W, et al.. A novel Retinex algorithm based on alternation direction optimization[C]. Sixth International Symposium on Precision Mechanical Measurements, Guiyang, China, 2013:1-6. [38] CHANG H B, NG M K, WANG W, et al.. Retinex image enhancement via a learned dictionary[J]. Optical Engineering, 2015, 54(1):1-15.https://www.researchgate.net/publication/273695163_Retinex_image_enhancement_via_a_learned_dictionary [39] 范日召, 何斌, 刘燕君, 等.基于广义线性系统和非锐化掩膜的图像增强算法[J].液晶与显示, 2016, 31(10):973-982.http://www.cnki.com.cn/Article/CJFDTOTAL-YJYS201610007.htmFAN R ZH, HE B, LIU Y J, et al.. Image enhancement algorithm based on generalized linear system and unsharp masking[J]. Chinese Journal of Liquid Crystals and Displays, 2016, 31(10):973-982. (in Chinese)http://www.cnki.com.cn/Article/CJFDTOTAL-YJYS201610007.htm [40] 李毅, 张云峰, 年轮, 等.尺度变化的Retinex红外图像增强[J].液晶与显示, 2016, 31(1):104-111.http://www.cnki.com.cn/Article/CJFDTOTAL-YJYS201601014.htmLI Y, ZHANG Y F, NIAN L, et al.. Infrared image enhancement method based on scale varies Retinex theory[J]. Chinese Journal of Liquid Crystals and Displays, 2016, 31(1):104-111. (in Chinese)http://www.cnki.com.cn/Article/CJFDTOTAL-YJYS201601014.htm [41] 赵文达, 赵建, 韩希珍, 等.基于变分偏微分方程的红外图像增强算法研究[J].液晶与显示, 2014, 29(2):281-285.http://www.cnki.com.cn/Article/CJFDTOTAL-YJYS201402023.htmZHAO W D, ZHAO J, HAN X ZH, et al.. Infrared image enhancement based on variational partial differential equations[J]. Chinese Journal of Liquid Crystals and Displays, 2014, 29(2):281-285. (in Chinese)http://www.cnki.com.cn/Article/CJFDTOTAL-YJYS201402023.htm [42] 陈莹, 朱明, 刘剑, 等.高斯混合模型自适应微光图像增强[J].液晶与显示, 2015, 30(2):300-309.http://www.cnki.com.cn/Article/CJFDTOTAL-YJYS201502019.htmCHEN Y, ZHU M, LIU J, et al.. Automatic low light level image enhancement using Gaussian mixture modeling[J]. Chinese Journal of Liquid Crystals and Displays, 2015, 30(2):300-309. (in Chinese)http://www.cnki.com.cn/Article/CJFDTOTAL-YJYS201502019.htm [43] 侯天娇, 郝志成, 朱明, 等.一种基于FPGA的彩色图像实时增强方法[J].液晶与显示, 2016, 31(12):1161-1167.http://www.cnki.com.cn/Article/CJFDTOTAL-YJYS201612011.htmHOU T J, HAO ZH CH, ZHU M, et al.. Real-time color image enhancement method based on FPGA[J]. Chinese Journal of Liquid Crystals and Displays, 2016, 31(12):1161-1167. (in Chinese)http://www.cnki.com.cn/Article/CJFDTOTAL-YJYS201612011.htm -
下载:
点击查看大图
图(2)/
表(2)
计量
- 文章访问数:4876
- HTML全文浏览量:1927
- PDF下载量:1428
- 被引次数:0
