A low-light image enhancement method with brightness balance and detail preservation

Abstract

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.

Enhancement of Traffic Images Under Different Weather Conditions Using Pynet

“…The general cause of low light can be caused by insufficient light sources, dark or shaded regions, and underground areas such as tunnels or mines. Several image enhancement methods are proposed for using the traditional algorithm such as Histogram Equalization, gamma correction, and retinex theory [31]. DriveRetinex-Net was used to enhance the low-light image as discussed in [32].…”

Perbaikan Kualitas Citra Cahaya Redup Menggunakan Teknik Perbaikan Histogram Equalization dan Adaptive Multi-scale Retinex

“…Menurut Nabuasa YY (2019), histogram equalization adalah metode yang bertujuan untuk meratakan distribusi intensitas piksel dalam citra guna mengatur tingkat kecerahan citra tersebut. Metode ini merupakan metode perbaikan histogram berdasarkan metode transformasi fungsi distribusi kumulatif (Li et al 2022;Gowda et al 2023). Perataan histogram ini didapatkan dengan cara mengubah derajat keabuan piksel (r) dengan derajat keabuan yang baru (s) menggunakan sebuah fungsi transformasi T, yang dapat dinyatakan dalam bentuk s = T(r).…”

“…AMSR dilakukan dengan membagi citra menjadi beberapa tingkat resolusi atau skala yang berbeda. Berikut adalah langkah-langkah dalam memperbaiki citra digital dengan metode AMSR (Li et al 2022):…”