### Low Rank and Sparse Decomposition and Its Application in Video and Image Processing

YANG Yongpeng, YANG Zhenzhen, LI Jianlin, LE Jun

1. 1.School of Network and Communication, Nanjing Vocational College of Information Technology, Nanjing 210023, China
2.National Engineering Research Center of Communications and Networking, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
• Online:2020-08-15 Published:2020-08-11

### 低秩稀疏分解及其在视频和图像处理中的应用

1. 1.南京信息职业技术学院 网络与通信学院，南京 210023
2.南京邮电大学 通信与网络技术国家工程研究中心，南京 210023

Abstract:

Low rank and sparse decomposition （LRSD） is a data representation technology and has been widely used in the field of computer vision and many other fields. The LRSD method is a mechanism which decomposes the known data matrix to the low rank and sparse components, and can be used to the practical applications such as video foreground and background separation, image denoising and so on. This paper gives these models, advantages and disadvantages of many LRSD methods based on the analysis of the current researches at home and abroad. Many methods are applied to the video foreground and background separation and image denoising. The experimental results of the video foreground and background separation include the extracted foreground objects, the F-measure values and the running time. The experimental results of image denoising include the denoising image, the PSNR values and the FSIM values. The results of the video foreground and background separation and image denoising show the advantages and disadvantages of these LRSD methods from the visual and quantitative perspectives.