直方图受限的窄动态范围彩色图像细节增强
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摘要
在彩色图像特别是窄动态范围的彩色图像增强中,为了保留更多图像细节,提出一种直方图受限的窄动态范围的彩色图像细节增强方法。该算法在RGB空间分别对三分量进行直方图受限运算,设置分量直方图的累积概率分布阈值C_T,将分量图像直方图分割成2个直方图H_1和H_2;将H_2(受限的直方图)非线性映射至H_1的均匀分布直方图中;合并RGB三分量输出彩色图像。实验结果表明,与同类算法相比,该算法在提高对比度的同时,具有最高的信息熵值,且输出的彩色图像视觉效果自然、清晰。
In order to preserve more image details in colour image enhancement, especially in narrow dynamic range, we proposed a histogram-limited color image detail enhancement for narrow dynamic range. The algorithm performed histogram constrained operation on three-components in RGB space and set the cumulative probability distribution threshold C_T of component histogram to divide the component image histogram into two histograms H_1 and H_2.We mapped H_2(constrained histogram) nonlinear to H_1 uniform distribution histogram, and merged three components of RGB to output color images. The experimental results show that compared with other similar algorithms, the proposed algorithm has the highest entropy value while improving the contrast, and the visual effect of the output color image is natural and clear.
In order to preserve more image details in colour image enhancement, especially in narrow dynamic range, we proposed a histogram-limited color image detail enhancement for narrow dynamic range. The algorithm performed histogram constrained operation on three-components in RGB space and set the cumulative probability distribution threshold C_T of component histogram to divide the component image histogram into two histograms H_1 and H_2.We mapped H_2(constrained histogram) nonlinear to H_1 uniform distribution histogram, and merged three components of RGB to output color images. The experimental results show that compared with other similar algorithms, the proposed algorithm has the highest entropy value while improving the contrast, and the visual effect of the output color image is natural and clear.
引文
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[2] 李赓飞,李桂菊,韩广良,等.亮通道先验Retinex对低照度图像的光照补偿[J].光学精密工程,2018,26(5):1191-1200.
[3] 钟志群,陈利.Retinex算法卫星遥感图像增强的应用[J].激光杂志,2016,37(10):106-110.
[4] 陈博洋.彩色遥感图像的亮度直方图局部线性化增强[J].光学精密工程,2017,25(2):502-508.
[5] 姜柏军,钟明霞.改进的直方图均衡化算法在图像增强中的应用[J].激光与红外,2014,44(6):703-706.
[6] Celik T,Tjahjadi T.Automatic Image Equalization and Contrast Enhancement Using Gaussian Mixture Modeling[J].IEEE Transactions on Image Processing,2011,21(1):145-156.
[7] Liu J H,Zhou C H,Chen P,et al.An efficient contrast enhancement method for remote sensing images[J].IEEE Geoscience and Remote Sensing Letters,2017,14(10):1715-1719.
[8] Wang X W,Chen L X.An effective histogram modification scheme for image contrast enhancement[J].Signal Processing:Image Communication,2017,58:187-198.
[9] Kim Y T.Contrast enhancement using brightness preserving bi-histogram equalization[J].IEEE Transactions on Consumer Electronics,1997,43(1):1-8.
[10] Wang Y,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.
[11] Chen S D,Ramli A R.Minimum mean brightness brror bi-histogramequalization in contrast enhancement[J].IEEE Transactions on Consumer Electronics,2003,49(4):1310-1319.
[12] Chen S D,Ramli A R.Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation[J].IEEE Transactions on Consumer Electronics,2004,49(4):1301-1309.
[13] Tang J R,Mat Isa N A.Bi-histogram equalization using modified histogram bins[J].Applied Soft Computing,2017,55:31-43.
[14] Zuiderveld K.Contrast limited adaptive histogram equalization[J].Graphic Gems IV San Diego:Academic Press Professional,1994:474-485.
[15] Ooi C H,Kong N S P,Ibrahim H.Bi-histogram equalization with a plateau limit for digital image enhancement[J].IEEE Transactions on Consumer Electronics,2010,55(4):2072-2080.
[16] Wang Y,Pan Z B.Image contrast enhancement using adjacent-blocks-based modification for local histogram equalization[J].Infrared Physics & Technology,2017,86:59-65.
[17] Liu S L,Rahman M A,Lin C F,et al.Image contrast enhancement based on intensity expansion-compression[J].Journal of Visual Communication and Image Representation,2017,48:169-181.
[18] Xiao B,Tang H,Jiang Y J,et al.Brightness and contrast controllable image enhancement based on histogram specification[J].Neurocomputing,2018,275:2798-2809.
[19] Sim K S,Tso C P,Tan Y Y.Recursive sub-image histogram equalization applied to gray scale images[J].Pattern Recognition Letters,2007,28(10):1209-1221.