Year: 2025
Type: article
Abstract: Although scholars have made significant progress in obtaining high dynamic range (HDR) images by using deep learning algorithms to fuse multiple exposure images, there are still challenges, such as image artifacts and distortion in high-brightness and low-brightness saturated areas. To this end, we propose a more detailed high dynamic range (MDHDR) method. Firstly, our proposed method uses super-resolution to enhance the details of long-exposure and short-exposure images and fuses them into medium-exposure images, respectively. Then, the HDR image is reconstructed by fusing the original medium-exposure, enhanced medium-exposure images. Extensive experimental results show that the proposed method can reconstruct good HDR images that perform better image clarity in quantitative tests and improve HDR-VDP2 by 4.8% in qualitative tests.
Source: Applied Sciences
DOI: 10.3390/app15115819
Authors: Kuo-Ching Hung, Sheng-Fuu Lin, Ching-Hung Lee
Institution: National Yang Ming Chiao Tung University
Language: English
Topic: Image Enhancement Techniques
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4410598191