Advances in Mathematical Physics

Advanced Image Processing and Analysis Solutions using PDE-based Modeling of the Physics Phenomena


Publishing date
01 Nov 2019
Status
Closed
Submission deadline
05 Jul 2019

Lead Editor

1Institute of Computer Science of the Romanian Academy, Iași, Romania

2“Al. I. Cuza” University, Iaşi, Romania

3“Gheorghe Asachi” Tehnical University, Iaşi, Romania

This issue is now closed for submissions.

Advanced Image Processing and Analysis Solutions using PDE-based Modeling of the Physics Phenomena

This issue is now closed for submissions.

Description

Partial differential equations (PDEs) have long been used to develop mathematical models in the physics of continuous media. Since these equations express continuous change, they have been used to model dynamical phenomena in heat conduction, elasticity, fluid mechanics, vibrating strings, electromagnetism, and other important physics and engineering fields.

Over the last 35 years, many such PDE-based models of physics phenomena have been successfully applied in both digital image processing and analysis and computer vision domains. Variational and nonvariational PDE-based techniques have been increasingly used in a variety of static and video image processing related fields, such as image restoration, inpainting, segmentation, compression, registration, and motion estimation, and have solved many challenges that still exist in these areas. Thus, PDEs have led to an entirely new image processing subdomain.

The major purpose of this special issue is to provide advanced research in these PDE-based image processing and analysis areas and to bring together the achievements of researchers in these fields. It aims to extend and improve the knowledge in these domains, by gathering articles disseminating novel research findings that answer the challenges that still remain in image denoising, interpolation, segmentation, (de)compression, and optical flow computation using continuous physics models like those based on nonlinear diffusion, reaction-diffusion, phase field, fluid, or Fokker–Planck equations. So, we encourage the authors to contribute original research articles describing new theoretical and practical accomplishments on relevant topics that are listed below, as well as review articles presenting the state of the art of the mentioned areas.

Potential topics include but are not limited to the following:

  • Nonlinear second and fourth order anisotropic diffusion models for image restoration
  • Image denoising and edge detection techniques using reaction-diffusion equations
  • Advanced image interpolation using variational and nonvariational PDE-based models
  • Structural inpainting approaches using fluid equations
  • Hybrid restoration and inpainting methods combining PDE schemes of various orders
  • Progressive halftoning solutions based on nonlinear diffusion equations
  • Partial differential equation-based compression and decompression techniques
  • Image segmentation solutions using phase-field models
  • Variational level-set based algorithms for image segmentation
  • Novel PDE-based solutions for optical flow estimation
  • Image processing and computer vision frameworks using Fokker–Planck equations
  • Novel variational models for image registration and fusion
Advances in Mathematical Physics
 Journal metrics
See full report
Acceptance rate16%
Submission to final decision138 days
Acceptance to publication22 days
CiteScore1.900
Journal Citation Indicator0.430
Impact Factor1.2
 Submit Check your manuscript for errors before submitting

Article of the Year Award: Impactful research contributions of 2022, as selected by our Chief Editors. Discover the winning articles.