Enhancement and Noise Suppression of Single Low-Light Grayscale Images
文献类型：期刊论文
| 作者 | T. Nie; X. F. Wang; H. X. Liu; M. X. Li; S. K. Nong; H. F. Yuan; Y. C. Zhao and L. Huang |
| 刊名 | Remote Sensing
 |
| 出版日期 | 2022 |
| 卷号 | 14期号:14页码:23 |
| DOI | 10.3390/rs14143398 |
| 英文摘要 | Low-light images have low contrast and high noise, making them not easily readable. Most existing image-enhancement methods focus on color images. In the present study, an enhancement and denoising algorithm for single low-light grayscale images is proposed. The algorithm is based on the multi-exposure fusion framework. First, on the basis of the low-light tone-mapping operators, the optimal virtual exposure image is constructed according to the information entropy criterion. Then, the latent low-rank representation is applied to two images to generate low-ranking parts and saliency parts to reduce noise after fusion. Next, the initial weight map is constructed based on the information contained in the decomposed images, and an adaptive weight refined algorithm is proposed to restore as much structural information as possible and keep the details while avoiding halo artifacts. When solving the weight maps, the decomposition and optimization of the nonlinear problem is converted into a total variation model, and an iterative method is used to reduce the computational complexity. Last, the normalized weight map is used for image fusion to obtain the enhanced image. The experimental results showed that the proposed method performed well both in the subjective and objective evaluation of state-of-the-art enhancement methods for low-light grayscale images. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.ciomp.ac.cn/handle/181722/66625]  |
| 专题 | 中国科学院长春光学精密机械与物理研究所 |
| 推荐引用方式 GB/T 7714 | T. Nie,X. F. Wang,H. X. Liu,et al. Enhancement and Noise Suppression of Single Low-Light Grayscale Images[J]. Remote Sensing,2022,14(14):23. |
| APA | T. Nie.,X. F. Wang.,H. X. Liu.,M. X. Li.,S. K. Nong.,...&Y. C. Zhao and L. Huang.(2022).Enhancement and Noise Suppression of Single Low-Light Grayscale Images.Remote Sensing,14(14),23. |
| MLA | T. Nie,et al."Enhancement and Noise Suppression of Single Low-Light Grayscale Images".Remote Sensing 14.14(2022):23. |
入库方式： OAI收割
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。