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Reseach Article

Image Enhancement using Vector Valued Image Processing

by Bhagyashree M. Kamble, Pankaj H.Durole
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 128 - Number 2
Year of Publication: 2015
Authors: Bhagyashree M. Kamble, Pankaj H.Durole
10.5120/ijca2015906431

Bhagyashree M. Kamble, Pankaj H.Durole . Image Enhancement using Vector Valued Image Processing. International Journal of Computer Applications. 128, 2 ( October 2015), 5-9. DOI=10.5120/ijca2015906431

@article{ 10.5120/ijca2015906431,
author = { Bhagyashree M. Kamble, Pankaj H.Durole },
title = { Image Enhancement using Vector Valued Image Processing },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 128 },
number = { 2 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 5-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume128/number2/22843-2015906431/ },
doi = { 10.5120/ijca2015906431 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:20:01.686798+05:30
%A Bhagyashree M. Kamble
%A Pankaj H.Durole
%T Image Enhancement using Vector Valued Image Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 128
%N 2
%P 5-9
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The images which consist of RGB color images is known as vector valued images. This images is the multimodal images which shows strong inter-channel correlation among each other. We treat this images by the new notion by introducing the spatial gradient channels. We can obtained the vector valued through minimizing the cost functional that penalizes the large angles. After this we introduce the Gateaux derivative that leads to diffusion gradient decent scheme. The cost functional gives the several examples of denoising and demosaicking. These shows that demosaicking will gives visually perfect image for the low noise by parallel level set preceded by denoising. We get the result that after introducing all the idea to the image we will yield the better result than any other approaches.

References
  1. Vector-Valued Image Processing by Parallel Level Sets Matthias Joachim Ehrhardt, Simon R. Arridge.
  2. B. K. Gunturk, Y. Altunbasak, and R. M. Mersereau, ``Color plane interpolation using alternating projections,'' IEEE Trans. Image Process., vol. 11,no. 9, pp. 997_1013, Sep. 2002.
  3. B. K. Gunturk, J. Glotzbach, Y. Altunbasak, R. W. Schafer, and R. M. Mersereau, ``Demosaicking: Color _lter array interpolation,'' IEEE Signal Process. Mag., vol. 22, no. 1, pp.44_54, Jan. 2005.
  4. Comparative Study of Demosaicing Algorithms for Bayer and Pseudo- Random Bayer Color Filter Arrays Georgi Zapryanov, Iva Nikolov.
  5. M. J. Ehrhardt and S. Arridge. (2013, Jul.). Vector-Valued Image Processing by Parallel Level Sets [Online].Available:http://www0.cs.ucl.ac.uk/staff/ehrhardt/software.html.
  6. Demosaicing: Image Reconstruction from Color CCD Samples Ron Kimmel.
Index Terms

Computer Science
Information Sciences

Keywords

vector valued images denoising demosaicking diffusion parallel level sets.