Anisotropic mesh adaptation for image representation

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4 Scopus citations

Abstract

Triangular meshes have gained much interest in image representation and have been widely used in image processing. This paper introduces a framework of anisotropic mesh adaptation (AMA) methods to image representation and proposes a GPRAMA method that is based on AMA and greedy-point removal (GPR) scheme. Different than many other methods that triangulate sample points to form the mesh, the AMA methods start directly with a triangular mesh and then adapt the mesh based on a user-defined metric tensor to represent the image. The AMA methods have clear mathematical framework and provide flexibility for both image representation and image reconstruction. A mesh patching technique is developed for the implementation of the GPRAMA method, which leads to an improved version of the popular GPRFS-ED method. The GPRAMA method can achieve better quality than the GPRFS-ED method but with lower computational cost.

Original languageEnglish (US)
Article number26
JournalEurasip Journal on Image and Video Processing
Volume2016
Issue number1
DOIs
StatePublished - Dec 1 2016

Keywords

  • Adaptive sampling
  • Anisotropic mesh adaptation
  • Image representation
  • Mesh patching
  • Metric tensor

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Electrical and Electronic Engineering

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