Publications by authors named "Yun-Sheng Qian"
Low-light images always suffer from dim overall brightness, low contrast, and low dynamic ranges, thus result in image degradation. In this paper, we propose an effective method for low-light image enhancement based on the just-noticeable-difference (JND) and the optimal contrast-tone mapping (OCTM) models. First, the guided filter decomposes the original images into base and detail images.
View Article and Find Full Text PDFEffective enhancement method of low-light-level images based on the guided filter and multi-scale fusion.
J Opt Soc Am A Opt Image Sci Vis
January 2023
Aiming to solve the problem of low-light-level (LLL) images with dim overall brightness, uneven gray distribution, and low contrast, in this paper, we propose an effective LLL image enhancement method based on the guided filter and multi-scale fusion for contrast enhancement and detail preservation. First, a base image and detail image(s) are obtained by using the guided filter. After this procedure, the base image is processed by a maximum entropy-based Gamma correction to stretch the gray level distribution.
View Article and Find Full Text PDFArticle Synopsis
- Tone mapping operators (TMOs) convert high dynamic range (HDR) images to low dynamic range (LDR) for better display on standard devices while keeping visual information intact.
- Current TMOs have limitations in handling diverse HDR images and require manual parameter adjustments for optimal quality.
- A new adaptive, parameter-free TMO is introduced, utilizing detail/base layer decomposition for improved dynamic range adjustment and detail enhancement, resulting in higher-quality tone-mapped images compared to existing methods.