![]() ![]() ![]() Received: JAccepted: DecemPublished: May 31, 2022Ĭopyright: © 2022 Li et al. PLoS ONE 17(5):Įditor: Gulistan Raja, University of Engineering & Technology, Taxila, PAKISTAN Experimental results show that the proposed method in this paper is better than the existing methods.Ĭitation: Li C, Zhu J, Bi L, Zhang W, Liu Y (2022) A low-light image enhancement method with brightness balance and detail preservation. Compared with the existing methods, the proposed algorithm significantly enhances the visual effect of the low-light images, based on human subjective evaluation and objective evaluation indices. Eventually, the final enhanced image is obtained by adding the mask with texture details to the image with balanced brightness and good contrast. On the other hand, the main structure of the image is extracted based on the total variation model, and the image mask with all the texture details is made by removing the main structure of the image. Finally, an image with balanced brightness and good contrast can be obtained. Then, the sub-histograms are clipped by two platforms and carried out the histogram equalization respectively. On the one hand, the image is processed by double histogram equalization with double automatic platform method based on improved cuckoo search (CS) algorithm, where the image histogram is segmented firstly, and the platform limit is selected according to the histogram statistics and improved CS technology. In this method, the image is processed bidirectionally. Traditional histogram equalization methods often lead to excessive enhancement and loss of details, thereby resulting in an unclear and unnatural appearance. This paper proposes a new method for low-light image enhancement with balancing image brightness and preserving image details, this method can improve the brightness and contrast of low-light images while maintaining image details. ![]()
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