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 language | English (US) |
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Article number | 26 |
Journal | Eurasip Journal on Image and Video Processing |
Volume | 2016 |
Issue number | 1 |
DOIs | |
State | Published - Dec 1 2016 |
Externally published | Yes |
Keywords
- Adaptive sampling
- Anisotropic mesh adaptation
- Image representation
- Mesh patching
- Metric tensor
ASJC Scopus subject areas
- Signal Processing
- Information Systems
- Electrical and Electronic Engineering