Abstract
Hyperspectral images (HSIs) are often corrupted by noise during the acquisition process, thus degrading the HSI's discriminative capability significantly. Therefore, HSI denoising becomes an essential preprocess step before application. This paper proposes a new HSI denoising approach connecting Partial Sum of Singular Values (PSSV) and superpixels segmentation named as SS-PSSV, which can remove the noise effectively. Based on the fact that there is a high correlation between different bands of the same signal, it is easy to know the property of low rank between distinct bands. To this end, PSSV is utilized, and in order to better tap the low-rank attribute of pixels, we introduce the superpixels segmentation method, which allows pixels in HSI with high similarity to be grouped in the same sub-block as much as possible. Extensive experiments display that the proposed algorithm outperforms the state-of-the-art.
| Original language | English |
|---|---|
| Pages (from-to) | 465-482 |
| Number of pages | 18 |
| Journal | Neurocomputing |
| Volume | 330 |
| DOIs | |
| Publication status | Published - 22 Feb 2019 |
Funding
The authors would like to thank the anonymous reviewers and AE for their constructive comments and suggestions, which improved the paper substantially. This work is supported by National Natural Science Foundation of China under Grant 61773302 and Shenzhen Fundamental Research fund under Grant JCYJ20160530141902978. Yang Liu received the B.Eng. degree from the Xidian University, Xi’an, China, in 2013. He is currently pursuing the Ph.D. degree with Xidian University, Xi’an, China. His research interests include dimensionality reduction, pattern recognition, and deep learning. Caifeng Shan (S’05M’08) received the B.Eng. degree in computer science from the University of Science and Technology of China, Hefei, China, in 2001, the M.Eng. degree in pattern recognition and intelligent system from the Institute of Automation, Chinese Academy of Sciences, Beijing, China, in 2004, and the Ph.D. degree in computer vision from the Queen Mary University of London,London, UK, in 2007. He is currently a Senior Scientist with Philips Research, Eindhoven, The Netherlands. He has authored about 50 technical papers and six patent applications. He edited two books Video Search and Mining (Berlin, Germany: Springer, 2010) and Multimedia Interaction and Intelligent User Interfaces: Principles, Methods and Applications (Springer, 2010). His current research interests include computer vision, pattern recognition, image video processing and analysis, machine learning, multimedia, and related applications. Dr. Shan has been the Guest Editor of the IEEE Transactions on Multimedia and Signal Processing (Elsevier). He organized several international workshops at flagship conferences such as IEEE ICCV and ACM Multimedia. He has served as a Program Committee Member and a Reviewer for numerous international conferences and journals. He was the recipient of the 2007 Chinese Government Award for Outstanding Self-Financed Students Abroad. Quanxue Gao received the B.Eng. degree from Xi’an Highway University, Xi’an, China, in 1998, the M.S. degree from the Gansu University of Technology, Lanzhou, China, in 2001, and the Ph.D. degree from Northwestern Polytechnical University, Xi’an, in 2005. He was an Associate Research with the Biometrics Center, The Hong Kong Polytechnic University, Hong Kong, from 2006 to 2007. From 2015 to 2016, he was a Visiting Scholar with the Department of Computer Science, The University of Texas at Arlington, Arlington, USA. He is currently a Professor with the School of Telecommunications Engineering, Xidian University, and also a Key Member of the State Key Laboratory of Integrated Services Networks. His current research interests include pattern recognition and machine learning. Xinbo Gao received the B.Eng., M.Sc., and Ph.D. degrees in signal and information processing from Xidian University, Xi’an, China, in 1994, 1997, and 1999, respectively. He was a Research Fellow with the Department of Computer Science, Shizuoka University, Shizuoka, Japan, from 1997 to 1998. From 2000 to 2001, he was a Post-Doctoral Research Fellow with the Department of Information Engineering, Chinese University of Hong Kong, Hong Kong. Since 2001, he has been with the School of Electronic Engineering, Xidian University. He is currently a Professor of pattern recognition and intelligent systems, and the Director of the State Key Laboratory of Integrated Services Networks, Xidian University. He has authored five books and around 150 technical articles in refereed journals and proceedings, including IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Systems, Man and Cybernetics, and Pattern Recognition in his areas of expertise. His current research interests include computational intelligence, machine learning, computer vision, pattern recognition and wireless communications. Jungong Han is a tenured Associate Professor of Data Science Institute at Lancaster University (LU), UK. In the past 15 years, he has been continuously conducting research in the fields of video analysis, computer vision and machine learning, and has published over 150 articles in leading journals and prestigious conferences, in which one of the firstauthored papers has been cited for more than 1000 times. Dr. Han is the member of the editorial board of several international journals, such as Elsevier Neurocomputing, Springer Multimedia Tools and Applications and IET Computer Vision, and has been (lead) Guest Editors for IEEE T-NNLS and IEEE T-CYB. Rongmei Cui received the B.Eng. degree from the Hebei University, Baoding, China, in 2015. She is currently pursuing the M. S. degree with Xidian University, Xi’an, China. Her research interests include image classification and machine learning.
Keywords
- Denoising
- Hyperspectral images
- PSSV
- Superpixel segmentation