Computer Science ›› 2015, Vol. 42 ›› Issue (Z11): 183-188.

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Foggy and Hazy Image Enhancement Algorithm Based on Retinex in Fuzzy Field

JIA Wei, LIU Yan-bin, LIU Wei, GE Geng-yu, SU Wen-li and FAN Li-lue   

  • Online:2018-11-14 Published:2018-11-14

Abstract: The traditional Retinex algorithm always products “halo” effect in fog and haze image enhancement,and has several shortcomings,such as the poor image exposure,image sharpness,image details,image fidelity and so on.In order to overcome these shortcomings of the traditional algorithm,we proposed a foggy and hazy image enhancement algorithm based on Retinex in the fuzzy field.Firstly,the original image was classified into several blocks using the proposed adaptive multi-threshold algorithm,and then the optimal crossover points of the image blocking areas were computed.Secondly,we used a novel linear membership function to map the image pixel value into fuzzy domain,then computed the correlation parameter of the fuzzy hyperbolic tangent function by crossover points,used the Retinex algorithm to perform no-linear image enhancement,and used the fuzzy hyperbolic tangent functions to adjust the enhancement result.Finally,the method of superposition of the linear was used to map the enhancement result into original image domain.The experimental result shows that the “halo” effect is suppressed,the proposed method plays a better role in the image sharpness,image details and image fidelity,and it has more widely applicability.

Key words: Fuzzy field,Foggy and hazy image enhancement,Retinex algorithm,Fuzzy hyperbolic tangent function

[1] Koschmieder H.Theorie der horizontalen sichtweite[J].Beitr.Phys.Freien Atm.,1924,12:171-181
[2] Narasimhan S G,Nayar S K.Vision and the atmosphere[J].International Journal of Computer Vision,2002,48(3):233-254
[3] Schechner Y Y,Narasimhan S G,Nayar S K.Instant dehazing of images using polarization[C]∥Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2001(CVPR 2001).IEEE,2001
[4] He K,Sun J,Tang X.Single image haze removal using darkchannel prior[J].IEEE Transactionson Pattern Analysis and Machine Intelligence,2011,33(12):2341-2353
[5] Lan X,Zhang L,Shen H,et al.Single image haze removal considering sensor blur and noise[J].EURASIP Journal on Advances in Signal Processing,2013,2013(1):1-13
[6] Serikawa S,Lu H.Underwater image dehazingusing joint trila-teral filter[J].Computers & Electrical Engineering,2014,40(1):41-50
[7] Land E H,McCann J.Lightness and Retinex theory[J].JOSA,1971,61(1):1-11
[8] Jobson D J,Rahman Z U,Woodell G A.Properties andperformance of center/surround Retinex[J].IEEE Transactions on Image Processing,1997,6(3):451-462
[9] Rahman Z U,Jobson D J,Woodell G A.Multi-scale Retinex for color image enhancement[C]∥Proceedings.International Conference on Image Processing,1996.IEEE,1996,3:1003-1006
[10] Rahman Z,Jobson D J,Woodell G A,et al.Image enhancement,image quality,and noise[C]∥International Society for Optics and Photonics Optics & Photonics 2005.2005
[11] 张新龙,汪荣贵,张璇,等.雾天图像增强计算模型及算法[J].中国图象图形学报,2011,16(8):1359-1368
[12] 李菊霞,余雪丽.雾天条件下的多尺度 Retinex图像增强算法[J].计算机科学,2013,40(3):299-301
[13] Pal S K,King R A.Image enhancement using fuzzy set[J].Electronics letters,1980,16(10):376-378
[14] Pal S K,King R A.On edge detection of X-ray images using fuzzy sets[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1983(1):69-77
[15] Pal S K,King R A.Image enhancement usig smoothing with fuzzy sets[J].IEEE Transactions on Systems,Man and Cybernetics-Part A:Systems and Humans,1981,11(7):494-501
[16] Otsu N.A threshold selection method from gray levelhistogram[J].IEEE Transactions on System,Man and Cybernetics,1979,9(1):62-66
[17] 刘艳,赵英良.Otsu 多阈值快速求解算法[J].计算机应用,2011,1(12):3363-3365
[18] Cheng H D,Sun Y.A hierarchical approach to color image segmentation using homogeneity[J].IEEE Transactions on Image Processing,2000,9(12):2071-2082
[19] Zhang H,Wang Z,Liu D.Chaotifying fuzzy hyperbolic modelusing adaptive inverse optimal control approach[J].International Journal of Bifurcation and Chaos,2004,14(10):3505-3517
[20] Wang Y,Zhang H.Robust H_∞ Control of Stochastic Hyperbolic Tangent Model [J].Journal of Northeastern University(Natural Science),2008,29(1):2
[21] 门绍雄,谭冠荣.图象的双曲正切函数变换[J].仪器仪表学报,1984,3:104-108
[22] 薛向阳,罗航哉.一种新的颜色相似度定义及其计算方法[J].计算机学报,1999,22(9):918-922

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