Graph Spectral Image Processing

被引：161
|
作者：
Cheung, Gene [1 ]
Magli, Enrico [2 ]
Tanaka, Yuichi [3 ,4 ]
Ng, Michael K. [5 ]
机构：
[1] Natl Inst Informat, Tokyo 1018430, Japan
[2] Politecn Torino, Dept Elect & Telecommun, Turin, Italy
[3] Tokyo Univ Agr & Technol, Grad Sch BASE, Koganei, Tokyo 1848588, Japan
[4] Japan Sci & Technol Agcy, PRESTO, Kawaguchi, Saitama 3320012, Japan
[5] Hong Kong Baptist Univ, Dept Math, Kowloon Tong, Hong Kong, Peoples R China
来源：
PROCEEDINGS OF THE IEEE | 2018年 / 106卷 / 05期
基金：
日本学术振兴会; 日本科学技术振兴机构;
关键词：
Graph signal processing; image processing; LEVEL SET METHOD; LAPLACIAN REGULARIZATION; ENERGY MINIMIZATION; FOURIER-TRANSFORM; WEIGHTED GRAPHS; ACTIVE CONTOURS; NONLOCAL IMAGE; NYSTROM METHOD; SPARSE; COMPRESSION;
D O I：
10.1109/JPROC.2018.2799702
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Recent advent of graph signal processing (GSP) has spurred intensive studies of signals that live naturally on irregular data kernels described by graphs (e.g., social networks, wireless sensor networks). Though a digital image contains pixels that reside on a regularly sampled 2-D grid, if one can design an appropriate underlying graph connecting pixels with weights that reflect the image structure, then one can interpret the image (or image patch) as a signal on a graph, and apply GSP tools for processing and analysis of the signal in graph spectral domain. In this paper, we overview recent graph spectral techniques in GSP specifically for image/video processing. The topics covered include image compression, image restoration, image filtering, and image segmentation.
引用
收藏
页码：907 / 930
页数：24
相关论文
共 50 条
  • [41] Mesh-based Image Retargeting with Spectral Graph Filtering
    Tanaka, Yuichi
    Yagyu, Saho
    Sakiyama, Akie
    Onuki, Masaki
    [J]. 2016 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA), 2016,
  • [42] Graph Convolutional Optimal Transport for Hyperspectral Image Spectral Clustering
    Liu, Shujun
    Wang, Huajun
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [43] Spatial-Spectral Clustering With Anchor Graph for Hyperspectral Image
    Wang, Qi
    Miao, Yanling
    Chen, Mulin
    Yuan, Yuan
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [44] AN INTRODUCTION TO SPECTRAL GRAPH TECHNIQUES FOR THE ANALYSIS OF HYPERSPECTRAL IMAGE DATA
    Gillis, David
    Messinger, David
    [J]. 2014 6TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2014,
  • [45] Spectral Graph Reduction for Efficient Image and Streaming Video Segmentation
    Galasso, Fabio
    Keuper, Margret
    Brox, Thomas
    Schiele, Bernt
    [J]. 2014 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2014, : 49 - 56
  • [46] Graph Cut Based Image Segmentation Method for Satellite Cloud Image Processing
    Fei Wenlong
    Lv Hong
    Wei Zhihui
    [J]. PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE OF MODELLING AND SIMULATION (ICMS2011), VOL 2, 2011, : 86 - 90
  • [47] Craquelure as a Graph: Application of Image Processing and Graph Neural Networks to the Description of Fracture Patterns
    Sidorov, Oleksii
    Hardeberg, Jon
    [J]. 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW), 2019, : 1429 - 1436
  • [48] A novel spectral clustering and its application in image processing
    [J]. Ruijun, G. (grj79@hotmail.com), 1600, International Hellenic University - School of Science (06):
  • [49] SPECTRAL IMAGE PROCESSING USING SPARSE LINEAR TRANSFORMS
    Robila, Stefan A.
    [J]. 2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, 2009, : 2914 - 2917
  • [50] METROLOGY OF IMAGE PROCESSING IN SPECTRAL REFLECTANCE MEASUREMENT BY UAV
    Honkavaara, E.
    Hakala, T.
    Markelin, L.
    Peltoniemi, J.
    [J]. EUROPEAN CALIBRATION AND ORIENTATION WORKSHOP (EUROCOW 2014), 2014, : 53 - 58
12345