基于Retinex理论的小波域图像增强方法研究
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摘要
图像增强作为图像处理中重要的预处理手段,由于其应用广泛,受到人们的广泛重视。所谓图像增强,是指有目的地强调图像像素的整体或局部取值特性,以改善图像视觉效果或满足特殊分析的需要。Retinex理论及相关算法是图像增强的新思路,其理论基础是色彩的恒常性,它通过模拟人眼观察场景的方式,恢复因图像采集设备限制而丢失的场景细节,达到增强图像对比度,还原物体真实色彩的目的。
本文以Retinex算法为研究重点,通过对传统的Retinex算法的分析,利用小波变换多分辨率的特点,提出了一种新的Retinex算法,并将Retinex理论引入JPEG2000压缩框架,用以增强JPEG2000压缩图像。文章主要内容如下：
1、通过从像素比较路径选择的角度出发,分析了Retinex算法一些常用的计算策略,包括基于随机路径的Retinex算法、基于迭代计算的McCann's Retinex算法、基于中心环绕的Retinex算法,并进行了实验对比分析。然后对经典Retinex计算方法进行了分析,指出Retinex算法的特点和局限性,并在实验中得到验证。
2、针对传统图像增强方法在图像增强的同时不能有效抑制噪声这一问题,本文根据小波变换多分辨率的特点,在Retinex理论基础上提出了图像亮度与噪声双估计模型的图像增强的新方法。该算法将图像小波分解后的低频系数进行波动抑制,对高频系数通过多子带独立系数模型进行亮度估计,同时使用不同的软-硬估计法对图像的噪声进行抑制。该方法不但能有效的提取图像的亮度信息,而且进行图像增强的同时能有效的抑制图像的噪声,且对于不同的雾天天气具有良好的自适应性。
3、在研究现有压缩图像增强算法的基础上,将Retinex理论引入到JPEG2000压缩框架中,达到增强JPEG2000压缩图像的目的,具体做法分为两个步骤：Retinex增强和改进亮度量化表。首先以Retinex理论为基础,将小波变换的低频系数看作入射光分量,高频系数看作反射光分量,通过修改低频系数来调整场景光照,修改高频系数来提高图像的对比度；然后通过判断各子块的活动性,自适应来修改亮度量化表,达到可以保留更多的细节,抑制块状效应的目的。
Image enhancement as an important pre-processing means has gained much attention by many people because of its widely used. Image enhancement is purposefully emphasized the gloable or local image pixel value features to improve the visual effect or to meet the specific analysis. Retinex theory and related algorithm is new idea of image enhancement.Retinex method is theoretically based on the color constancy of human visual system. The basic strategy is simulating the process of human vision to enhance image contrast and resume true color of object.
This paper proposed a new Retinex algorithm and JPEG2000 compression framework by analysising the traditional Retinex algorithm and wavelet multi-resolution features. Secondly a new method to enhance JPEG2000 compressed image is proposed, in which Retinex theory is introduced into JPEG2000 compressed frame.
The main content of this thesis is shown as follow:
1.Based on the view of selecting the path of pixels comparison, Common Computational Strategies of Retinex algorithm has been analysised, including Retinex algorithm based on random paths, the McCann's Retinex algorithm based on iterative calculation, the Retinex algorithm based on center/surround, Then this paper pointed out characteristics and limitations of Retinex algorithm, and verified in experiments.
2.Because of the problem that the traditional enhancement algorithm can not suppress the noise effectively when enhanced the image. This paper proposes a novel algorithm of estimating the image illumination and noise in the wavelet domain based on Retinex theory. By using the feature of the wavelet multi-resolution, algorithm suppress the volatility of the low-frequency coefficient and use the model of multi-subband independent coefficient to estimate the high-frequency coefficient, at the same time using soft-hard estimated method to suppress the image noise. The experimental results show that the algorithm can extract the image illuminate vector effectively, but also can suppress the image noise and adapt in different foggy weather.
3.In the base of recently research for image enhancement algorithm in the compressed domain, we introduce the Retinex theory into the JPEG2000 code process to achievie the goal for enhancement the JPEG2000 compression image. The procedure may divide into two steps. First, using the Retinex algorithm to carry on the enhancement; Secondly,improving the Luminance quantification table.It take the Retinex theory as the foundation,regarding the DC coefficient of DWT coefficient as the incident light component and the AC coefficient of DWT coefficient as the reflected light component.the goal for revises the DC coefficient is to adjust the scene illumination condition and for the AC coefficient is to enhance the image contrast gradient,then judging the activity of the great block to adjust the luminance quantification table adaptively to achieve the goal of preserving enhancement detail and suppressing the massive effect.
本文以Retinex算法为研究重点,通过对传统的Retinex算法的分析,利用小波变换多分辨率的特点,提出了一种新的Retinex算法,并将Retinex理论引入JPEG2000压缩框架,用以增强JPEG2000压缩图像。文章主要内容如下：
1、通过从像素比较路径选择的角度出发,分析了Retinex算法一些常用的计算策略,包括基于随机路径的Retinex算法、基于迭代计算的McCann's Retinex算法、基于中心环绕的Retinex算法,并进行了实验对比分析。然后对经典Retinex计算方法进行了分析,指出Retinex算法的特点和局限性,并在实验中得到验证。
2、针对传统图像增强方法在图像增强的同时不能有效抑制噪声这一问题,本文根据小波变换多分辨率的特点,在Retinex理论基础上提出了图像亮度与噪声双估计模型的图像增强的新方法。该算法将图像小波分解后的低频系数进行波动抑制,对高频系数通过多子带独立系数模型进行亮度估计,同时使用不同的软-硬估计法对图像的噪声进行抑制。该方法不但能有效的提取图像的亮度信息,而且进行图像增强的同时能有效的抑制图像的噪声,且对于不同的雾天天气具有良好的自适应性。
3、在研究现有压缩图像增强算法的基础上,将Retinex理论引入到JPEG2000压缩框架中,达到增强JPEG2000压缩图像的目的,具体做法分为两个步骤：Retinex增强和改进亮度量化表。首先以Retinex理论为基础,将小波变换的低频系数看作入射光分量,高频系数看作反射光分量,通过修改低频系数来调整场景光照,修改高频系数来提高图像的对比度；然后通过判断各子块的活动性,自适应来修改亮度量化表,达到可以保留更多的细节,抑制块状效应的目的。
Image enhancement as an important pre-processing means has gained much attention by many people because of its widely used. Image enhancement is purposefully emphasized the gloable or local image pixel value features to improve the visual effect or to meet the specific analysis. Retinex theory and related algorithm is new idea of image enhancement.Retinex method is theoretically based on the color constancy of human visual system. The basic strategy is simulating the process of human vision to enhance image contrast and resume true color of object.
This paper proposed a new Retinex algorithm and JPEG2000 compression framework by analysising the traditional Retinex algorithm and wavelet multi-resolution features. Secondly a new method to enhance JPEG2000 compressed image is proposed, in which Retinex theory is introduced into JPEG2000 compressed frame.
The main content of this thesis is shown as follow:
1.Based on the view of selecting the path of pixels comparison, Common Computational Strategies of Retinex algorithm has been analysised, including Retinex algorithm based on random paths, the McCann's Retinex algorithm based on iterative calculation, the Retinex algorithm based on center/surround, Then this paper pointed out characteristics and limitations of Retinex algorithm, and verified in experiments.
2.Because of the problem that the traditional enhancement algorithm can not suppress the noise effectively when enhanced the image. This paper proposes a novel algorithm of estimating the image illumination and noise in the wavelet domain based on Retinex theory. By using the feature of the wavelet multi-resolution, algorithm suppress the volatility of the low-frequency coefficient and use the model of multi-subband independent coefficient to estimate the high-frequency coefficient, at the same time using soft-hard estimated method to suppress the image noise. The experimental results show that the algorithm can extract the image illuminate vector effectively, but also can suppress the image noise and adapt in different foggy weather.
3.In the base of recently research for image enhancement algorithm in the compressed domain, we introduce the Retinex theory into the JPEG2000 code process to achievie the goal for enhancement the JPEG2000 compression image. The procedure may divide into two steps. First, using the Retinex algorithm to carry on the enhancement; Secondly,improving the Luminance quantification table.It take the Retinex theory as the foundation,regarding the DC coefficient of DWT coefficient as the incident light component and the AC coefficient of DWT coefficient as the reflected light component.the goal for revises the DC coefficient is to adjust the scene illumination condition and for the AC coefficient is to enhance the image contrast gradient,then judging the activity of the great block to adjust the luminance quantification table adaptively to achieve the goal of preserving enhancement detail and suppressing the massive effect.
引文
[1]阮秋琦.数字图像处理[M].电子工业出版社,2001.
[2]冈萨雷斯.数字图像处理(第二版)[M].电子工业出版社,2003.
[3]章毓晋.图像处理和分析[M].清华大学出版社,1999.
[4]石美红,张军英,李永刚,吴戴明.一种新的低对比度图像增强的方法[J].计算机应用研究,2005,(1)：235-238.
[5]季娜.基于DSP的雾天监控视频图像清晰化处理方法研究[D].大连：大连海事大学,2009.
[6]王彦臣,李树杰,黄康卿.基于多尺度Retinex的数字X光图像增强方法研究[J].光学精密工程,2006,14(1)：70-77.
[7]储昭辉.图像压缩编码方法综述[J].电脑知识与技术,2009,5(18)：4785-4788.
[8]Gregory K, Wallace. The JPEG still picture compression standard[J]. IEEE transactions on consumer electronics,1991.
[9]Y Luo and R K Wars. Removing the blocking artifacts of blockbased DCT compressed images [J]. IEEE Trans. Image Process.,2003, vol.12, no.7:838-842.
[10]J Tang, J Kim, and Eli Peli. Image enhancement in the JPEG domain for people with vision impairment[J]. IEEE Trans. Biomedical Engineering,2004, vol.51, no.11: 2013-2023.
[11]E Land and J McCann. Lightness and retinex theory [J]. Opt. Soc.Amer., Jan.1971, vol. 61,no.1:1-11.
[12]Jobson D J, Rahman Z U, Woodell G A. Properties and performance of a center/surround retinex[J]. IEEE Transactions on Image Processing,1997,6(3) 451-462.
[13]Jobson D J, Rahman Z, Woodell G A. The statistics of visual representation [J]. SPIE. 2002,4736:25-35.
[14]洪明坚.图像增强的自适应直方图修正算法研究及其应用[D],重庆：重庆大学,2002
[15]MOH'D BELAL AL-ZOUBI, AMMAR M KAMEL, MAKKI J RADHY. Techniques for Image Enhancement in the Spatial Domain[J]. WSEAS Transactions on Computers.2006,5(5).
[16]胡琼,汪荣贵,胡韦伟,杨万挺.基于直方图分割的彩色图像增强算法[J].中国图象图形学报,2009(9)：1776-1781.
[17]Kim J Y, Kim L S, Hwang S H. An advanced contrast enhancement using partially overlapped Sub-Block histogram equalization [J]. IEEE Transcations On Circuits And Systems For Video Technology, April 2001,11(4):475-484.
[18]Wan Yu, Chen Qian, and Zhang Bao-Min. Image enhancement based on equal area dualistic sub-image histogram equalization method[J]. IEEE Transactions on Consumer Electronics,1999,45(1):68-75.
[19]Soong-Der Chen,Ramli A.R.Minimum mean brightness error bi-histogram equalization in contrast enhancement [J]. IEEE Transactions on Consumer Electronics 2003,49(4).
[20]江巨浪,张佑生等.保持图像亮度的局部直方图均衡算法[J].电子学报,2006,34(5),861-866.
[21]Qing Wang, Ward R K. Fast Image/Video Contrast Enhancement Based on Weighted Thresholded Histogram Equalization[J]. IEEE Tansactions on Consumer Electronics. 2007,53(2):757-764.
[22]K.S.Sim, C.P.Tso, Y.Y.Tan. Recursive sub-image histogram equalization applied to gray scale images[J]. ScienceDirect, Pattern Recognition Letters,2007(28):1209-1221.
[23]Ibrahim H.,Kong N.S.P.Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement. IEEE Tansactions on Consumer Electronics.2007, 53(4).
[24]Sengee N, Heung Choi. Brightness preserving weight clustering histogram equalization[J]. Consumer Electronics,IEEE Transactions on.2008(3):1329-1337.
[25]Z.Rahman,D.J.Jobson,and G.A.Woodell. Retinex processing for au-tomatic image enhancement[J]. J. Electron. Imag.,2004,13(1):100-110.
[26]Edwin H Land. The retinex theory of color vision [J]. Scientific American, 1977,237(6):108-129.
[27]Marsi S, Impoco G, Ukovich A,et al. Using a Recursive Rational Filter to Enhance Color Images [J].IEEE Transcations On Instrumentation And Measurement.2008,57(6):1230-1236.
[28]B.Funt and F.Ciurea. Tuning Retinex parameters [J]. J.Electron.Imag., vol.13, no.1,pp.58-64,2004.
[29]R. Kimmel, M. Elad, D. Shaked, K. Renato, I. Sobel. A variational framework for Retinex[J]. Int. J. Comp. Vision 2003,52(1):7-23.
[30]Rahman Z, Jobson D J, Woodell G A. Multi-scale retinex for color image enhancement [C]//proceedings of Image Processing,1996.Processings, International Conference on, Piscataway:IEEE press,1996,3:1003-1006.
[31]M. Ogata, T. Tsuchiya, T. Kubozono, K. Ueda. Dynamic range compression based on illumination compensation. IEEE Trans[J]. Consumer Electron., vol. 47, no.3, pp.548-558, Aug.2001.
[32]Vivek Agarwal. Achieving Color Constancy and Illumination Compensation[C]. ECE 574.2003.
[33]J.L.Starck, F.Murtaph,E.J.Candes,D.L.Donoho.Gray and Color Image Contrast Enhancement by the Curvelet Transform [J]. IEEE Trans. on Image Processing, 2003,12(6):706—716.
[34]Doron Shaked. Interpolation of Non-Linear Retinex Type Algorithms[C]. HP Laboratories Israel, HPL-2006-179 December 4,2006.
[35]Doo Hyun Choi, Ick Hoon Jang. Color Image Enhancement Based on Single-Scale Retinex With a JND-Based Nonlinear Filter [C]//proceedings of Circuits and Systems,2007.ISCAS 2007. IEEE International Symposium on, Piscataway:IEEE press,2007:3948-3951.
[36]Bo Sun, Weifang Chen, Hongyu Li, Wenjing Tao, Jiang Li. Modified Luminance Based Adaptive MSR[C]. Fourth International Conference on Image and Graphics,2007,pp.116-120.
[37]Provenzi E, Fierro M, Rizzi A, De Carli L, et al. Random spray Retinex:a new Retinex implementation to investigate the local properties of the model[J]. IEEE Tansactions, Image Processing,2007,16(1):162-171.
[38]Wen Wang, Bo Li, Jin Zheng, Shu Xian, Jing Wang. A Fast Multi-scale Retinex Algorithm for Color Image Enhancement[C]. Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition, Hong Kong,30-31 Aug.2008.
[39]王耀南,李树涛,毛建旭.计算机图像处理与识别技术[M].高等教育出版社,2001.
[40]孙延奎.小波分析及其应用[M].机械工业出版社2005.
[41]陈传峰,朱长仁,宋洪芹.基于巴特沃斯低通滤波器的图像增强[J].现代电子技术,2007,30(24).
[42]蒙军,索中乐,陈洪,时新华.一种改进的红外图像增强方法[J].解放军理工大学学报,2004,5(5).
[43]韩丽娜,熊杰,耿国华,周明全.利用HSV空间的双通道同态滤波真彩图像增强[J].计算机工程与应用,2009,45(27).
[44]张新明,沈兰荪.基于小波的同态滤波用于图像对比度增强[J].电子学报,2001,29(4).
[45]Ming-Jung Seow, Vijayan K. Asari:Ratio rule and homomorphic filter for enhancement of digital colour image. Neurocomputing,2006,69(7-9):954-958.
[46]Uche Nnolim, Peter Lee. Homomorphic Filtering of colour images using a Spatial Filter Kernel in the HSI colour space[J].2008, IEEE Instrumentation and Measurement Technology Conference, Pages 1334-1776.
[47]S. S. O.Steven S. O. Choy, Y.-H.Yuk-Hee Chan, andW.-C.Wan-Chi Siu. Reduction of block-transform image coding artifacts by using local statistics of transform coefficients[J]. IEEE Signal Processing Letters, vol.4, no.1, pp. 5-7, Jan.1997.
[48]J. Tang, E. Peli, and S. Acton. Image enhancement using a contrast measure in the compressed domain[J]. IEEE Signal Process. Lett., vol.10, no.10, pp. 289-292, Oct.2003.
[49]K Iqbal, A Chaudhry, A Khan, and A Bangash. Multiscale contrast enhancement for compressed digital images with block artifacts consideration [J]. Innovations and Advanced Techniques in Computer and Information Sciences and Engineering,2007:267-272.
[50]Sangkeun Lee,An Efficient Content-Based Image Enhancement in the Compressed Domain Using Retinex Theory[J]. IEEE Transcations On Circuits and Systems for Video Technology,2007,17(2).
[51]Jayanta Mukhopadhyay, Sanjit K. Mitra:Color enhancement in the compressed domain. ICIP2008:3144-3147
[52]刘方敏,吴永辉,俞建新.JPEG2000图像压缩过程及原理概述[J].计算机辅助设计与图形学学报,2002,14(10).
[53]吴颖谦,施鹏飞.基于小波变换的低对比度图像增强[J].红外与激光工程,2003,32(1).
[54]Abdelwahab, Ahmed A.Ahmed, Mohamed K.Hashem, Somaya H. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform[J]. Radio Science Conference,2007,24th National; Cairo, Egypt.
[55]王正友,胡国胜,吴海燕.基于DWT的Alpha-Rooting图像增强[J].小型微型计算机系统,2009,(05)：996-999.
[56]Jinshan Tang,Rangaraj M. Rangayyan, Jun Jun Xu,Issam EI-Naqa. Yongyi Yang:Computer-Aided Detection and Diagnosis of Breast Cancer With Mammography:Recent Advances[J]. IEEE Transcations On Information Technology in Biomedicine,2009,13(2):236-251.
[57]贾明桥.大雾天气下图像的清晰化方法[D].西安：西安理工大学,2006.
[58]肖燕峰.基于Retinex理论的图像增强恢复算法研究[D].上海：上海交通大学,2007.
[59]任斌.基于Retinex图像增强算法研究与实现[D].南京：南京理工大学,2009.
[60]王大雷.雾天图像增强技术的分析与研究[D].南京：南京理工大学,2007.
[61]涂雅瑗.雾天降质图像的对比度增强方法研究[D].大连：大连海事大学,2009.
[62]Oakly J P, Satherly B L. Improving images quality in poor visibility condition using physicak model for degradation[J]. IEEE Trans.on Image Processing, 1998,7(2):167-179.
[63]O.Creutzfeld, B.Lange-Malecki, and K.Wortmann. Darkness induction, Retinex and cooperative mechanisms invision[J]. Exp.BrainRes., vol.67, pp.270-283,1987.
[64]E.Provenzi, L.D.Carli, A.Rizzi, andD.Marini. Mathematical definition and analysis of the Retinex algorithm[J]. J.Opt.Soc.Amer.A, vol.22, pp.2613-2621, 2005.
[65]李郁,闫敬文.一种基于小波分析的SAR图像增强去噪方法[J].计算机工程与设计,2004,25(2).
[66]Donoho D L, Johnstone I M. Ideal Spatial Adaptation via wavelet shrinkage [J]. Biometrika,1994,14(6):425-455.
[67]Mihcak M K, Kozintsev I, Ramchandran K. Low-complexity image denoising based on statistical modeling of wavelet coefficients [J]. IEEE signal processing Letter,1999,6(2):300-303.
[68]Vidakovic B, Lozoya C B. On time-depentent wavelet denoising[J]. IEEE tansction on signal processing,1998,46(9):2549-2551.
[69]林哲民等.在小波阈中进行图像噪声方差估计的EM方法[J].红外与毫米波学报,2001,20(6)：199～202.
[70]陈武凡.小波分析及其在图像处理中的应用[M].科学出版社,2002,50～175.
[71]陶布曼JPEG2000图像压缩基础、标准和实践[M].电子工业出版社,2004：486-520.
[72]苏岱安JPEG2000图像压缩的研究[D].湖南：湖南大学,2007.
[73]宋涛,郭树旭,李伟JPEG2000及其编码系统的实现[J].现代电子技术,2005,9：47～49.
[74]吴永辉,俞建新JPEG2000图像压缩算法概述及网络应用前景.计算机工程,2003,29(3)：7-10.
[75]张旭东,卢国栋,冯健.图像编码基础和小波压缩技术[M].清华大学出版社,2004：112-119.
[76]D.Taubman.High Performance Scalable Image Compression with EBCOT. IEEE Transactionson Image Processing,2000,9(7):1158-1170.
[77]唐跃林,肖沙里等.一种反映人眼视觉特性的JPEG压缩编码[J].微型机与应用,2004,2：49～50.
[78]颜培玉.肺部CT影像增强算法的研究与实现[D].沈阳：沈阳航空工业学院,2009.
[79]覃庆炎.简牍数字图像增强算法研究与应用[D].成都：成都理工大学,2008.
[80]曾强华.基于JPEG2000的静态图像压缩的研究[D].辽宁：辽宁工程技术大学,2003.
[81]张萌.基于FPGA的JPEG2000提升格式小波变换结构研究[D].西北：西北工业大学,2004.
[82]王明翠.SPIHT算法的改进及均值均方差在静态图像压缩中的应用[D].青岛：青岛科技大学,2007.
[2]冈萨雷斯.数字图像处理(第二版)[M].电子工业出版社,2003.
[3]章毓晋.图像处理和分析[M].清华大学出版社,1999.
[4]石美红,张军英,李永刚,吴戴明.一种新的低对比度图像增强的方法[J].计算机应用研究,2005,(1)：235-238.
[5]季娜.基于DSP的雾天监控视频图像清晰化处理方法研究[D].大连：大连海事大学,2009.
[6]王彦臣,李树杰,黄康卿.基于多尺度Retinex的数字X光图像增强方法研究[J].光学精密工程,2006,14(1)：70-77.
[7]储昭辉.图像压缩编码方法综述[J].电脑知识与技术,2009,5(18)：4785-4788.
[8]Gregory K, Wallace. The JPEG still picture compression standard[J]. IEEE transactions on consumer electronics,1991.
[9]Y Luo and R K Wars. Removing the blocking artifacts of blockbased DCT compressed images [J]. IEEE Trans. Image Process.,2003, vol.12, no.7:838-842.
[10]J Tang, J Kim, and Eli Peli. Image enhancement in the JPEG domain for people with vision impairment[J]. IEEE Trans. Biomedical Engineering,2004, vol.51, no.11: 2013-2023.
[11]E Land and J McCann. Lightness and retinex theory [J]. Opt. Soc.Amer., Jan.1971, vol. 61,no.1:1-11.
[12]Jobson D J, Rahman Z U, Woodell G A. Properties and performance of a center/surround retinex[J]. IEEE Transactions on Image Processing,1997,6(3) 451-462.
[13]Jobson D J, Rahman Z, Woodell G A. The statistics of visual representation [J]. SPIE. 2002,4736:25-35.
[14]洪明坚.图像增强的自适应直方图修正算法研究及其应用[D],重庆：重庆大学,2002
[15]MOH'D BELAL AL-ZOUBI, AMMAR M KAMEL, MAKKI J RADHY. Techniques for Image Enhancement in the Spatial Domain[J]. WSEAS Transactions on Computers.2006,5(5).
[16]胡琼,汪荣贵,胡韦伟,杨万挺.基于直方图分割的彩色图像增强算法[J].中国图象图形学报,2009(9)：1776-1781.
[17]Kim J Y, Kim L S, Hwang S H. An advanced contrast enhancement using partially overlapped Sub-Block histogram equalization [J]. IEEE Transcations On Circuits And Systems For Video Technology, April 2001,11(4):475-484.
[18]Wan Yu, Chen Qian, and Zhang Bao-Min. Image enhancement based on equal area dualistic sub-image histogram equalization method[J]. IEEE Transactions on Consumer Electronics,1999,45(1):68-75.
[19]Soong-Der Chen,Ramli A.R.Minimum mean brightness error bi-histogram equalization in contrast enhancement [J]. IEEE Transactions on Consumer Electronics 2003,49(4).
[20]江巨浪,张佑生等.保持图像亮度的局部直方图均衡算法[J].电子学报,2006,34(5),861-866.
[21]Qing Wang, Ward R K. Fast Image/Video Contrast Enhancement Based on Weighted Thresholded Histogram Equalization[J]. IEEE Tansactions on Consumer Electronics. 2007,53(2):757-764.
[22]K.S.Sim, C.P.Tso, Y.Y.Tan. Recursive sub-image histogram equalization applied to gray scale images[J]. ScienceDirect, Pattern Recognition Letters,2007(28):1209-1221.
[23]Ibrahim H.,Kong N.S.P.Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement. IEEE Tansactions on Consumer Electronics.2007, 53(4).
[24]Sengee N, Heung Choi. Brightness preserving weight clustering histogram equalization[J]. Consumer Electronics,IEEE Transactions on.2008(3):1329-1337.
[25]Z.Rahman,D.J.Jobson,and G.A.Woodell. Retinex processing for au-tomatic image enhancement[J]. J. Electron. Imag.,2004,13(1):100-110.
[26]Edwin H Land. The retinex theory of color vision [J]. Scientific American, 1977,237(6):108-129.
[27]Marsi S, Impoco G, Ukovich A,et al. Using a Recursive Rational Filter to Enhance Color Images [J].IEEE Transcations On Instrumentation And Measurement.2008,57(6):1230-1236.
[28]B.Funt and F.Ciurea. Tuning Retinex parameters [J]. J.Electron.Imag., vol.13, no.1,pp.58-64,2004.
[29]R. Kimmel, M. Elad, D. Shaked, K. Renato, I. Sobel. A variational framework for Retinex[J]. Int. J. Comp. Vision 2003,52(1):7-23.
[30]Rahman Z, Jobson D J, Woodell G A. Multi-scale retinex for color image enhancement [C]//proceedings of Image Processing,1996.Processings, International Conference on, Piscataway:IEEE press,1996,3:1003-1006.
[31]M. Ogata, T. Tsuchiya, T. Kubozono, K. Ueda. Dynamic range compression based on illumination compensation. IEEE Trans[J]. Consumer Electron., vol. 47, no.3, pp.548-558, Aug.2001.
[32]Vivek Agarwal. Achieving Color Constancy and Illumination Compensation[C]. ECE 574.2003.
[33]J.L.Starck, F.Murtaph,E.J.Candes,D.L.Donoho.Gray and Color Image Contrast Enhancement by the Curvelet Transform [J]. IEEE Trans. on Image Processing, 2003,12(6):706—716.
[34]Doron Shaked. Interpolation of Non-Linear Retinex Type Algorithms[C]. HP Laboratories Israel, HPL-2006-179 December 4,2006.
[35]Doo Hyun Choi, Ick Hoon Jang. Color Image Enhancement Based on Single-Scale Retinex With a JND-Based Nonlinear Filter [C]//proceedings of Circuits and Systems,2007.ISCAS 2007. IEEE International Symposium on, Piscataway:IEEE press,2007:3948-3951.
[36]Bo Sun, Weifang Chen, Hongyu Li, Wenjing Tao, Jiang Li. Modified Luminance Based Adaptive MSR[C]. Fourth International Conference on Image and Graphics,2007,pp.116-120.
[37]Provenzi E, Fierro M, Rizzi A, De Carli L, et al. Random spray Retinex:a new Retinex implementation to investigate the local properties of the model[J]. IEEE Tansactions, Image Processing,2007,16(1):162-171.
[38]Wen Wang, Bo Li, Jin Zheng, Shu Xian, Jing Wang. A Fast Multi-scale Retinex Algorithm for Color Image Enhancement[C]. Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition, Hong Kong,30-31 Aug.2008.
[39]王耀南,李树涛,毛建旭.计算机图像处理与识别技术[M].高等教育出版社,2001.
[40]孙延奎.小波分析及其应用[M].机械工业出版社2005.
[41]陈传峰,朱长仁,宋洪芹.基于巴特沃斯低通滤波器的图像增强[J].现代电子技术,2007,30(24).
[42]蒙军,索中乐,陈洪,时新华.一种改进的红外图像增强方法[J].解放军理工大学学报,2004,5(5).
[43]韩丽娜,熊杰,耿国华,周明全.利用HSV空间的双通道同态滤波真彩图像增强[J].计算机工程与应用,2009,45(27).
[44]张新明,沈兰荪.基于小波的同态滤波用于图像对比度增强[J].电子学报,2001,29(4).
[45]Ming-Jung Seow, Vijayan K. Asari:Ratio rule and homomorphic filter for enhancement of digital colour image. Neurocomputing,2006,69(7-9):954-958.
[46]Uche Nnolim, Peter Lee. Homomorphic Filtering of colour images using a Spatial Filter Kernel in the HSI colour space[J].2008, IEEE Instrumentation and Measurement Technology Conference, Pages 1334-1776.
[47]S. S. O.Steven S. O. Choy, Y.-H.Yuk-Hee Chan, andW.-C.Wan-Chi Siu. Reduction of block-transform image coding artifacts by using local statistics of transform coefficients[J]. IEEE Signal Processing Letters, vol.4, no.1, pp. 5-7, Jan.1997.
[48]J. Tang, E. Peli, and S. Acton. Image enhancement using a contrast measure in the compressed domain[J]. IEEE Signal Process. Lett., vol.10, no.10, pp. 289-292, Oct.2003.
[49]K Iqbal, A Chaudhry, A Khan, and A Bangash. Multiscale contrast enhancement for compressed digital images with block artifacts consideration [J]. Innovations and Advanced Techniques in Computer and Information Sciences and Engineering,2007:267-272.
[50]Sangkeun Lee,An Efficient Content-Based Image Enhancement in the Compressed Domain Using Retinex Theory[J]. IEEE Transcations On Circuits and Systems for Video Technology,2007,17(2).
[51]Jayanta Mukhopadhyay, Sanjit K. Mitra:Color enhancement in the compressed domain. ICIP2008:3144-3147
[52]刘方敏,吴永辉,俞建新.JPEG2000图像压缩过程及原理概述[J].计算机辅助设计与图形学学报,2002,14(10).
[53]吴颖谦,施鹏飞.基于小波变换的低对比度图像增强[J].红外与激光工程,2003,32(1).
[54]Abdelwahab, Ahmed A.Ahmed, Mohamed K.Hashem, Somaya H. Image Enhancement Using a Contrast measure in the Discrete Wavelet Transform[J]. Radio Science Conference,2007,24th National; Cairo, Egypt.
[55]王正友,胡国胜,吴海燕.基于DWT的Alpha-Rooting图像增强[J].小型微型计算机系统,2009,(05)：996-999.
[56]Jinshan Tang,Rangaraj M. Rangayyan, Jun Jun Xu,Issam EI-Naqa. Yongyi Yang:Computer-Aided Detection and Diagnosis of Breast Cancer With Mammography:Recent Advances[J]. IEEE Transcations On Information Technology in Biomedicine,2009,13(2):236-251.
[57]贾明桥.大雾天气下图像的清晰化方法[D].西安：西安理工大学,2006.
[58]肖燕峰.基于Retinex理论的图像增强恢复算法研究[D].上海：上海交通大学,2007.
[59]任斌.基于Retinex图像增强算法研究与实现[D].南京：南京理工大学,2009.
[60]王大雷.雾天图像增强技术的分析与研究[D].南京：南京理工大学,2007.
[61]涂雅瑗.雾天降质图像的对比度增强方法研究[D].大连：大连海事大学,2009.
[62]Oakly J P, Satherly B L. Improving images quality in poor visibility condition using physicak model for degradation[J]. IEEE Trans.on Image Processing, 1998,7(2):167-179.
[63]O.Creutzfeld, B.Lange-Malecki, and K.Wortmann. Darkness induction, Retinex and cooperative mechanisms invision[J]. Exp.BrainRes., vol.67, pp.270-283,1987.
[64]E.Provenzi, L.D.Carli, A.Rizzi, andD.Marini. Mathematical definition and analysis of the Retinex algorithm[J]. J.Opt.Soc.Amer.A, vol.22, pp.2613-2621, 2005.
[65]李郁,闫敬文.一种基于小波分析的SAR图像增强去噪方法[J].计算机工程与设计,2004,25(2).
[66]Donoho D L, Johnstone I M. Ideal Spatial Adaptation via wavelet shrinkage [J]. Biometrika,1994,14(6):425-455.
[67]Mihcak M K, Kozintsev I, Ramchandran K. Low-complexity image denoising based on statistical modeling of wavelet coefficients [J]. IEEE signal processing Letter,1999,6(2):300-303.
[68]Vidakovic B, Lozoya C B. On time-depentent wavelet denoising[J]. IEEE tansction on signal processing,1998,46(9):2549-2551.
[69]林哲民等.在小波阈中进行图像噪声方差估计的EM方法[J].红外与毫米波学报,2001,20(6)：199～202.
[70]陈武凡.小波分析及其在图像处理中的应用[M].科学出版社,2002,50～175.
[71]陶布曼JPEG2000图像压缩基础、标准和实践[M].电子工业出版社,2004：486-520.
[72]苏岱安JPEG2000图像压缩的研究[D].湖南：湖南大学,2007.
[73]宋涛,郭树旭,李伟JPEG2000及其编码系统的实现[J].现代电子技术,2005,9：47～49.
[74]吴永辉,俞建新JPEG2000图像压缩算法概述及网络应用前景.计算机工程,2003,29(3)：7-10.
[75]张旭东,卢国栋,冯健.图像编码基础和小波压缩技术[M].清华大学出版社,2004：112-119.
[76]D.Taubman.High Performance Scalable Image Compression with EBCOT. IEEE Transactionson Image Processing,2000,9(7):1158-1170.
[77]唐跃林,肖沙里等.一种反映人眼视觉特性的JPEG压缩编码[J].微型机与应用,2004,2：49～50.
[78]颜培玉.肺部CT影像增强算法的研究与实现[D].沈阳：沈阳航空工业学院,2009.
[79]覃庆炎.简牍数字图像增强算法研究与应用[D].成都：成都理工大学,2008.
[80]曾强华.基于JPEG2000的静态图像压缩的研究[D].辽宁：辽宁工程技术大学,2003.
[81]张萌.基于FPGA的JPEG2000提升格式小波变换结构研究[D].西北：西北工业大学,2004.
[82]王明翠.SPIHT算法的改进及均值均方差在静态图像压缩中的应用[D].青岛：青岛科技大学,2007.