Graph Learning on Images using Kron-Reduction

Please enable javascript in your browser.

Eini, Mohammad | 2024

0 Viewed

Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 57307 (05)
University: Sharif University of Technology
Department: Electrical Engineering
Advisor(s): Amini, Arash
Abstract:
In this project, we are going to face the problem of learning a graph on images with big sizes which has many applications in image processing like image segmentation. There are two main obstacles to doing so. One is the fact that the task of graph learning becomes immensely time-consuming when we have a large number of nodes. The other is the memory shortage since most computers do not have rams with big capacities, which is a requirement when the number of nodes is too high. We are going to suggest two suboptimal solutions for finding a sparse graph on images with respect to smoothness criteria on the Laplacian matrix of the acquired graph and reduce the time needed for this task. Then we will suggest an alternative way of optimisation when performing a graph learning algorithm to reduce the memory requirement at any needed step
Keywords:
Graph Learning ; Image Processing ; Image Segmentation ; Sparse Graphs ; Image Denoising ; Graph Laplacian

No TOC