A Nighttime and Daytime Single-Image Dehazing Method

• Published in: Applied sciences Vol. 13; no. 1; p. 255
• Main Authors: Tang, Yunqing, Xiang, Yin, Chen, Guangfeng
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2023
• Subjects: Daytime; daytime dehazing; Deep learning; high-light area transmission compensation; Illumination; Image contrast; Image processing; Image quality; Light; Light sources; Methods; mixed-filter; nighttime dehazing; Regularization
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app13010255

In this study, the requirements for image dehazing methods have been put forward, such as a wider range of scenarios in which the methods can be used, faster processing speeds and higher image quality. Recent dehazing methods can only unilaterally process daytime or nighttime hazy images. However, we propose an effective single-image technique, dubbed MF Dehazer, in order to solve the problems associated with nighttime and daytime dehazing. This technique was developed following an in-depth analysis of the properties of nighttime hazy images. We also propose a mixed-filter method in order to estimate ambient illumination. It is possible to obtain the color and light direction when estimating ambient illumination. Usually, after dehazing, nighttime images will cause light source diffusion problems. Thus, we propose a method to compensate for the high-light area transmission in order to improve the transmission of the light source areas. Then, through regularization, the images obtain better contrast. The experimental results show that MF Dehazer outperforms the recent dehazing methods. Additionally, it can obtain images with higher contrast and clarity while retaining the original color of the image.