An improved image enhancement algorithm: Radial contrast-limited adaptive histogram equalization

• Published in: Multimedia tools and applications 2024, Vol.83 (36), p.83695-83707
• Main Authors: Hu, Chunsheng, Li, Hao, Ma, Teng, Zeng, Cailian, Ji, Xiaoli
• Format: Article
• Language: English
• Subjects: Adaptive algorithms; Algorithms; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Entropy (Information theory); Equalization; Histograms; Image contrast; Image enhancement; Image processing; Image quality; Image segmentation; Multimedia Information Systems; Special Purpose and Application-Based Systems
• ISSN: 1573-7721; 1380-7501; 1573-7721
• DOI: 10.1007/s11042-024-18922-5

A commonly used method in image enhancement is Contrast-Limited Adaptive Histogram Equalization, which is simple and fast. However, this algorithm is to segment the image into multiple rectangular areas, and then perform the image processing, this method works poorly when working on images with poor radial contrast, prone to local image information loss, and the characteristics of the whole image information are of poor quality after being processed. In this paper, we proposed a histogram equalization method of radial ring segmentation image, aiming at the image enhancement processing of less obvious radial contrast. Compared with the classical HE and CLAHE algorithms, the algorithm proposed in this paper can effectively enhance the information entropy of the processed images by an average of 12%. As a result, the images carry more information and exhibit richer texture features. Moreover, the contrast enhancement effect is improved, and the brightness of the images is more moderate.