Graph Spectral Image Processing

English | 2021 | ISBN: 1789450284 | 325 pages | True PDF | 11.49 MB
Graph spectral image processing is the study of imaging data from a graph frequency perspective. Modern image sensors capture a wide range of visual data including high spatial resolution/high bit-depth 2D images and videos, hyperspectral images, light field images and 3D point clouds. The field of graph signal processing - extending traditional Fourier analysis tools such as transforms and wavelets to handle data on irregular graph kernels - provides new flexible computational tools to analyze and process these varied types of imaging data. Recent methods combine graph signal processing ideas with deep neural network architectures for enhanced performances, with robustness and smaller memory requirements.