Sparse representation based medical ultrasound images denoising with reshaped-RED | |
Pu, Xiaoqiu1,2; Li, Zhixin1,2; Li, Baopeng1; Lei, Hao1; Gao, Wei1; Liu, Jiwei1,2 | |
2019 | |
会议日期 | 2019-05-10 |
会议地点 | Guangzhou, China |
关键词 | Ultrasound image speckle noise sparse representation regularization by denoising variable splitting |
卷号 | 11179 |
DOI | 10.1117/12.2540245 |
英文摘要 | Medical ultrasound images are usually corrupted by the noise during their acquisition known as speckle. Speckle noise removal is a key stage in medical ultrasound image processing. Due to the ill-posed feature of image denoising, many regularization methods have been proved effective. This paper introduces an approach which collaborate both sparse dictionary learning and regularization method to remove the speckle noise. The method trains a redundant dictionary by an efficient dictionary learning algorithm, and then uses it in an image prior regularization model to obtain the recovered image. Experimental results demonstrate that the proposed model has enhanced performance both in despeckling and texture-preserving of medical ultrasound images compared to some popular methods. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. |
产权排序 | 1 |
会议录 | Eleventh International Conference on Digital Image Processing, ICDIP 2019 |
会议录出版者 | SPIE |
语种 | 英语 |
ISSN号 | 0277786X;1996756X |
ISBN号 | 9781510630758 |
内容类型 | 会议论文 |
源URL | [http://ir.opt.ac.cn/handle/181661/31869] |
专题 | 西安光学精密机械研究所_空间光学应用研究室 |
作者单位 | 1.Space Optics Laboratory, Xi'An Institute of Optics and Precision Mechanics of CAS, Xi'an; 710119, China; 2.University of Chinese Academy of Sciences, Beijing; 100049, China |
推荐引用方式 GB/T 7714 | Pu, Xiaoqiu,Li, Zhixin,Li, Baopeng,et al. Sparse representation based medical ultrasound images denoising with reshaped-RED[C]. 见:. Guangzhou, China. 2019-05-10. |
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