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Reseach Article

Comparison of Random Impulse Noise Detection Techniques

Published on June 2015 by Avanti A. Parchand, Anagha G. Savant, Ankit S.kale
National Conference on Emerging Trends in Advanced Communication Technologies
Foundation of Computer Science USA
NCETACT2015 - Number 4
June 2015
Authors: Avanti A. Parchand, Anagha G. Savant, Ankit S.kale
2178cc18-6192-445d-9a51-af5fc3302487

Avanti A. Parchand, Anagha G. Savant, Ankit S.kale . Comparison of Random Impulse Noise Detection Techniques. National Conference on Emerging Trends in Advanced Communication Technologies. NCETACT2015, 4 (June 2015), 28-31.

@article{
author = { Avanti A. Parchand, Anagha G. Savant, Ankit S.kale },
title = { Comparison of Random Impulse Noise Detection Techniques },
journal = { National Conference on Emerging Trends in Advanced Communication Technologies },
issue_date = { June 2015 },
volume = { NCETACT2015 },
number = { 4 },
month = { June },
year = { 2015 },
issn = 0975-8887,
pages = { 28-31 },
numpages = 4,
url = { /proceedings/ncetact2015/number4/21007-2052/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Emerging Trends in Advanced Communication Technologies
%A Avanti A. Parchand
%A Anagha G. Savant
%A Ankit S.kale
%T Comparison of Random Impulse Noise Detection Techniques
%J National Conference on Emerging Trends in Advanced Communication Technologies
%@ 0975-8887
%V NCETACT2015
%N 4
%P 28-31
%D 2015
%I International Journal of Computer Applications
Abstract

In this project we are presenting techniques to detect random value impulse noise from color image. The paper compares the computational time required for finding the noisy pixels. From this the efficiency of the system can be determined. The main goal of this paper is to reduce the running time of detection stage by comparing the two techniques: Directional Detector (DD) and Euclidean distance method. The performance criteria of detection technique are verified using Recall, Specificity, Accuracy and Precision.

References
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  2. Subramoniam, M. , and V. Rajini. "Statistical feature based classification of arthritis in knee X-ray images using local binary pattern. " Circuits, Power and Computing Technologies (ICCPCT), 2013 International Conference on. IEEE, 2013.
  3. R. Gonzalez and E. Richard Woods, ?"Digital Image Research bulletin of Jordan ACM,vol II
  4. Mrs. C. Mythili and Dr. V. Kavitha,''Efficient Technique for Color Image Noise Reduction", the Research bulletin of Jordan ACM,vol II
  5. Liwei Wang, Yan Zhang, Jufu Feng," On the Euclidean Distance of Images" NNSF (60175004) and NKBRSF (2004CB318005).
  6. N. Selvarasu, Alamelu Nachiappan and N. M. Nandhitha," Euclidean Distance Based Color Image Segmentation of Abnormality Detection from Pseudo Color Thermographs", International Journal of Computer Theory and Engineering, Vol. 2, No. 4, August, 20101793-8201
  7. Rafael C. Gonzalez ,Richard E. Woods, Steven L. Eddins. -"Digital Image Processing Using MATLAB",second edition, Pearson education, 2003.
Index Terms

Computer Science
Information Sciences

Keywords

Impulse Noise Impulse Noise Detection Using Directional Detector Euclidean Distance