Paper Info
Title
A new GVF-based image enhancement formulation for use in the presence of mixed noise
Abstract
This paper is concerned with the introduction of a new gradient vector flow (GVF) field formulation that shows increased robustness in the presence of mixed noise and with its evaluation when included in the development of image enhancement algorithms. In this regard, the main contribution associated with this work resides in the development of an adaptive image enhancement framework that couples the anisotropic diffusion models with the adaptive median filtering that is designed for the restoration of digital images corrupted with mixed noise. To further illustrate the advantages associated with the proposed GVF field formulation, additional experiments are conducted when the proposed strategy is applied in the construction of anisotropic models for texture enhancement.
Year
DOI
Venue
2010
10.1016/j.patcog.2010.02.023
Pattern Recognition
Keywords
Field
DocType
image enhancement algorithm,anisotropic diffusion model,field formulation,texture enhancement,digital image,proposed gvf field formulation,anisotropic model,anisotropic diffusion,adaptive image enhancement framework,adaptive median,shock filters,new gvf-based image enhancement,mixed noise,gvf
Anisotropic diffusion,Computer vision,Anisotropy,Median filter,Pattern recognition,Robustness (computer science),Digital image,Vector flow,Mixed noise,Artificial intelligence,Mathematics
Journal
Volume
Issue
ISSN
43
8
Pattern Recognition
Citations 
PageRank 
References 
21
0.74
19
Authors
2
Name
Order
Citations
PageRank
Ovidiu Ghita123418.12
Paul F. Whelan256139.95