Efficient Retinex-Based Low-Light Image Enhancement Through Adaptive Reflectance Estimation and LIPS Postprocessing

In this paper, a novel Retinex-based low-light image enhancement method is proposed, in which it has two parts: reflectance component estimation and logarithmic image processing subtraction (LIPS) enhancement. The enhancement processing is performed in the V channel of the color HSV space. First, adaptive parameter bilateral filters are used to get more accurate illumination layer data, instead of Gaussian filter. Moreover, the weighting estimation method is used to calculate the adaptive parameter to adjust the removal of the illumination and obtain the reflectance by just-noticeable-distortion (JND) factor. In this way, it can effectively prevent the over-enhancement in high-brightness regions. Then, the logarithmic image processing subtraction (LIPS) method based on maximum standard deviation of the histogram is applied to enhance reflectance component part, where the interval of the parameter is according to the cumulative distribution function (CDF). Experimental results demonstrate that the proposed method outperforms other competitive methods in terms of subjective and objective assessment.