Application of partial differential equations in image processing

DOI

10.2991/icemct-16.2016.291How to use a DOI?

Keywords

Structure tensor; Nonlinear edge enhancement; Image denoising; Nonlocal operator.

Abstract

Based on the superiority of PDE and its physical mechanism analysis from image processing, combining variational methods, functional analysis, differential geometry, projective geometry and other mathematical tools to the image denoising smoothing, image segmentation, image restoration, image to enlarge , image reconstruction, medical image processing, remote sensing image processing and other fields are widely used. Especially nonlinear diffusion equation has a very important role in image processing and machine vision. This paper focuses on the theme of image de-noising and enhancement of several PDE-based image denoising and enhancement model for analysis and improvement. It discusses the anisotropic diffusion method causes agglomeration and some solutions, and diffusion equation with a nonlinear structure tensor combined spread function and select the appropriate parameters to establish an improved model for image edge enhancement. While the model spread function and the key parameters were discussed, and numerical experiments to verify the feasibility of the method.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaoke Cui
PY  - 2016/04
DA  - 2016/04
TI  - Application of partial differential equations in image processing
BT  - Proceedings of the 2016 International Conference on Education, Management and Computing Technology (ICEMCT-16)
PB  - Atlantis Press
SP  - 1383
EP  - 1387
SN  - 2352-5398
UR  - https://doi.org/10.2991/icemct-16.2016.291
DO  - 10.2991/icemct-16.2016.291
ID  - Cui2016/04
ER  -