Bracketing Image Restoration and Enhancement with High-Low Frequency Decomposition
文献类型：预印本
| 作者 | Chen, Genggeng4; Dai, Kexin3; Yang, Kangzhen3; Hu, Tao3,4; Chen, Xiangyu2; Yang, Yongqing1; Dong, Wei4; Wu, Peng3; Zhang, Yanning3; Yan, Qingsen3 |
| 英文摘要 | In real-world scenarios, due to a series of image degradations, obtaining high-quality, clear content photos is challenging. While significant progress has been made in synthesizing high-quality images, previous methods for image restoration and enhancement often overlooked the characteristics of different degradations. They applied the same structure to address various types of degradation, resulting in less-than-ideal restoration outcomes. Inspired by the notion that high/low frequency information is applicable to different degradations, we introduce HLNet, a Bracketing Image Restoration and Enhancement method based on high-low frequency decomposition. Specifically, we employ two modules for feature extraction: shared weight modules and non-shared weight modules. In the shared weight modules, we use SCConv to extract common features from different degradations. In the non-shared weight modules, we introduce the High-Low Frequency Decomposition Block (HLFDB), which employs different methods to handle high-low frequency information, enabling the model to address different degradations more effectively. Compared to other networks, our method takes into account the characteristics of different degradations, thus achieving higher-quality image restoration. Copyright © 2024, The Authors. All rights reserved. |
| 出处 | arXiv |
| 出版者 | arXiv |
| ISSN号 | 23318422 |
| 发表日期 | 2024-04-21 |
| 语种 | 英语 |
| 产权排序 | 4 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/97473]  |
| 专题 | 空天技术处 |
| 作者单位 | 1.Xi'an Institute of Optics and Precision Mechanics of CAS, China 2.University of Macau, China; 3.Northwestern Polytechnical University, China; 4.Xi'an University of Architecture and Technology, China; |
| 推荐引用方式 GB/T 7714 | Chen, Genggeng,Dai, Kexin,Yang, Kangzhen,et al. Bracketing Image Restoration and Enhancement with High-Low Frequency Decomposition. 2024. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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