Graph Spectral Image Processing

Gene Cheung*, Enrico Magli, Yuichi Tanaka, Kwok Po NG

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

169 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)907-930
Number of pages24
JournalProceedings of the IEEE
Issue number5
Publication statusPublished - 1 May 2018

Scopus Subject Areas

  • Electrical and Electronic Engineering

User-Defined Keywords

  • Graph signal processing
  • image processing


Dive into the research topics of 'Graph Spectral Image Processing'. Together they form a unique fingerprint.

Cite this