Color Image Denoising Based on Low-Rank Tensor Train
文献类型：会议论文
| 作者 | Zhang Y(张杨)1,2,3; Han Z(韩志)2,3 ; Tang YD(唐延东)2,3
|
| 出版日期 | 2018 |
| 会议日期 | December 12-14, 2018 |
| 会议地点 | Chengdu, China |
| 关键词 | Image denoising low rank tensor train tensor networks color image |
| 页码 | 1-6 |
| 英文摘要 | Tensor has been widely used in computer vision due to its ability to maintain spatial structure information. Owning to the well-balanced unfolding matrices, the recently proposed tensor train (TT) decomposition can make full use of information from tensors. Thereby, tensor train representation has a better performance in many fields compared to traditional methods of tensor decomposition. Inspired by the success of tensor train, in this paper, we firstly apply low-rank tensor train to recovering noisy color images. Meanwhile, we propose a novel algorithm for noise-contaminated images based on the block coordinate descent (BCD) method. The numerical experiments demonstrate that our algorithm can give a better result in the real color image both visually and numerically |
| 产权排序 | 1 |
| 会议录 | 2018 10th International Conference on Graphics and Image Processing (ICGIP 2018)
 |
| 会议录出版者 | SPIE |
| 会议录出版地 | Bellingham, USA |
| 语种 | 英语 |
| ISSN号 | 0277-786X |
| ISBN号 | 978-1-5106-2828-1 |
| WOS记录号 | WOS:000485096200095 |
| 源URL | [http://ir.sia.cn/handle/173321/23847]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Zhang Y(张杨) |
| 作者单位 | 1.University of Chinese Academy of Sciences, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, China 3.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, China |
| 推荐引用方式 GB/T 7714 | Zhang Y,Han Z,Tang YD. Color Image Denoising Based on Low-Rank Tensor Train[C]. 见:. Chengdu, China. December 12-14, 2018. |
入库方式： OAI收割
来源：沈阳自动化研究所
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。