基于双边伽马校正的保亮度图像增强方法
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摘要
图像增强的许多实际应用需要保持输入图像的亮度,因此提出基于伽马校正及多尺度图像融合的保亮度图像增强方法。分析伽马校正曲线对图像中过暗和过亮区域的影响,设计能够同时改善过暗和过亮区域对比度的双边伽马校正曲线。对双边伽马校正所生成的两幅校正图像进行多尺度图像融合,其中低频子带图像采用加权平均融合规则以保持亮度,高频子带图像采用平均选取融合规则以突出细节。该方法是一种空频域相结合的保亮度图像增强方法。实验结果表明,该方法在避免过增强、保亮度和突出细节三方面均取得良好效果,且优于一些经典的基于直方图均衡化思想的图像增强方法。
Maintaining the brightness of input images are required to many practical applications of image enhancement. Therefore, this paper presented a brightness preserving image enhancement method based on gamma correction and multi-scale image fusion. We designed bi-gamma correction curves to improve the contrast of over-bright and over-dark regions by analyzing the influence of gamma correction curve on both regions. Then, these two revised images, generated by bi-gamma correction, were integrated by multi-scale image fusion. A weighted average fusion rule was adopted for low frequency sub-band images to keep brightness, and an average and selection fusion rule was adopted for high frequency sub-band images to highlight details. This method was performed by a combination of spatial and frequency domain. Experimental results indicate that this method yields good performance in three aspects of avoiding over-enhancement, preserving brightness and enhancing details, and outperforms some image enhancement methods based on the concept of histogram equalization.
Maintaining the brightness of input images are required to many practical applications of image enhancement. Therefore, this paper presented a brightness preserving image enhancement method based on gamma correction and multi-scale image fusion. We designed bi-gamma correction curves to improve the contrast of over-bright and over-dark regions by analyzing the influence of gamma correction curve on both regions. Then, these two revised images, generated by bi-gamma correction, were integrated by multi-scale image fusion. A weighted average fusion rule was adopted for low frequency sub-band images to keep brightness, and an average and selection fusion rule was adopted for high frequency sub-band images to highlight details. This method was performed by a combination of spatial and frequency domain. Experimental results indicate that this method yields good performance in three aspects of avoiding over-enhancement, preserving brightness and enhancing details, and outperforms some image enhancement methods based on the concept of histogram equalization.
引文
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[4] Magudeeswaran V,Ravichandran C G,Thirumurugan P.Brightness preserving bi‐level fuzzy histogram equalization for MRI brain image contrast enhancement[J].International Journal of Imaging Systems & Technology,2017,27(2):153-161
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[6] Chen S D,Ramli A R.Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation[J].IEEE Transactions on Consumer Electronics,2003,49(4):1301-1309.
[7] Wang Y,Chen Q,Zhang B.Image enhancement based on equal area dualistic sub-image histogram equalization method[J].IEEE Transactions on Consumer Electronics,1999,45(1):68-75.
[8] Kim Y T.Contrast enhancement using brightness preserving bi-histogram equalization[J].IEEE Transactions on Consumer Electronics,1997,43(1):1-8.
[9] Yao Z,Lai Z,Wang C,et al.Brightness preserving and contrast limited bi-histogram equalization for image enhancement[C]//International Conference on Systems and Informatics.IEEE,2017:866-870.
[10] Jordanski M,Arsic A,Tuba M.Dynamic recursive subimage histogram equalization algorithm for image contrast enhancement[C]//Telecommunications Forum Telfor.IEEE,2016:819-822.
[11] Yao Z,Lai Z,Wang C,et al.Brightness preserving and contrast limited bi-histogram equalization for image enhancement[C]//International Conference on Systems and Informatics.IEEE,2017:866-870.
[12] Li H,Qiu H,Yu Z,et al.Infrared and visible image fusion scheme based on NSCT and low-level visual features[J].Infrared Physics & Technology,2016,76:174-184.
[13] Shi Y,Yang J,Wu R.Reducing Illumination Based on Nonlinear Gamma Correction[C]//IEEE International Conference on Image Processing.IEEE,2007:I-529-I-532.
[14] Kubinger W,Vincze M,Ayromlou M.The role of gamma correction in colour image processing[C]//9th European Signal Processing Conference(EUSIPCO 1998).IEEE,1998.
[15] Jagger W S,Muntz W R.Aquatic vision and the modulation transfer properties of unlighted and diffusely lighted natural waters[J].Vision Research,1993,33(13):1755-1763.
[16] Chou C H,Li Y C.A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile[J].IEEE Transactions on Circuits and Systems for Video Technology,2002,5(6):467-476.
[17] Burt P J,Kolczynski R J.Enhanced image capture through fusion[C]//1993(4th) International Conference on Computer Vision.IEEE,1993:173-182.
[18] CVG-URG[DB/OL].http://decsai.ugr.es/cvg/dbimagenes.
[19] Burt P J,Adelson E H.The Laplacian pyramid as a compact image code[J].IEEE Transactions on Communications,1983,31(4):532-540.
[20] 牛爽,尚媛园,丁辉,等.基于亮度传播图的低照度图像增强算法[J].计算机应用与软件,2016,33(6):168-171.
[21] 王淑青,姚伟,陈进,等.基于直方图均衡化与形态学处理的边缘检测[J].计算机应用与软件,2016,33(3):193-196.
[22] 全永奇,邓家先,寇计萍,等.一种新的NSCT域图像增强算法[J].计算机应用与软件,2016,33(3):206-209,221.
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