School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
PLoS One. 2022 May 31;17(5):e0262478. doi: 10.1371/journal.pone.0262478. eCollection 2022.
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. Traditional histogram equalization methods often lead to excessive enhancement and loss of details, thereby resulting in an unclear and unnatural appearance. In this method, the image is processed bidirectionally. 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. Then, the sub-histograms are clipped by two platforms and carried out the histogram equalization respectively. Finally, an image with balanced brightness and good contrast can be obtained. 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. Eventually, the final enhanced image is obtained by adding the mask with texture details to the image with balanced brightness and good contrast. 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. Experimental results show that the proposed method in this paper is better than the existing methods.
本文提出了一种新的低光图像增强方法，该方法可以在保持图像细节的同时平衡图像亮度和对比度。传统的直方图均衡化方法往往会导致过度增强和细节丢失，从而导致图像不清晰和不自然。在该方法中，图像被双向处理。一方面，图像通过基于改进布谷鸟搜索（CS）算法的双自动平台方法进行双直方图均衡化处理，其中首先对图像直方图进行分段，并根据直方图统计和改进 CS 技术选择平台限制。然后，通过两个平台对子直方图进行裁剪，并分别进行直方图均衡化。最终，可以得到一个亮度平衡、对比度良好的图像。另一方面，基于全变分模型提取图像的主要结构，并通过去除图像的主要结构来制作具有所有纹理细节的图像遮罩。最终，通过将具有纹理细节的遮罩添加到具有平衡亮度和良好对比度的图像中，得到最终的增强图像。与现有的方法相比，所提出的算法显著提高了低光图像的视觉效果，基于人类主观评价和客观评价指标。实验结果表明，本文提出的方法优于现有的方法。
