Automatic low light level image enhancement using Gaussian mixture modeling

In order to improve the output quality of visible light sensor in low-light environment,an adaptive image enhancement algorithm using Gaussian mixture modeling is proposed in this paper.The histogram of image is modeled with Gaussian mixture modeling and the improved EM algorithm is used to fit the histogram and get the best parameters.Then,the histogram is separated into sub-histograms based on the intersections of Gaussian components.Finally,the mapping is achieved according to the parameters of output image,and the final enhanced image is obtained by the maximum entropy preserving method which tends to the characteristics of human visual.The experimental results show that the algorithm can determine the optimal number of clusters adaptively and improve the speed of the histogram fitting which costs 0.37 saveragely.Comparing with traditional methods,the enhancement result is superior in terms of objective evaluations of related information entropy and texture information.It can improve the contrast of the low light level image and maintain the details.