CFP last date
20 May 2024
Reseach Article

Analysis of Non-linear Filtering Techniques based on Quantitative Metrics using Different Images

by Rajkumar S, Vijayarajan V, Shrey Gupta, Anil Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 52 - Number 6
Year of Publication: 2012
Authors: Rajkumar S, Vijayarajan V, Shrey Gupta, Anil Kumar
10.5120/8205-1606

Rajkumar S, Vijayarajan V, Shrey Gupta, Anil Kumar . Analysis of Non-linear Filtering Techniques based on Quantitative Metrics using Different Images. International Journal of Computer Applications. 52, 6 ( August 2012), 13-20. DOI=10.5120/8205-1606

@article{ 10.5120/8205-1606,
author = { Rajkumar S, Vijayarajan V, Shrey Gupta, Anil Kumar },
title = { Analysis of Non-linear Filtering Techniques based on Quantitative Metrics using Different Images },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 52 },
number = { 6 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 13-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume52/number6/8205-1606/ },
doi = { 10.5120/8205-1606 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:51:33.743914+05:30
%A Rajkumar S
%A Vijayarajan V
%A Shrey Gupta
%A Anil Kumar
%T Analysis of Non-linear Filtering Techniques based on Quantitative Metrics using Different Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 52
%N 6
%P 13-20
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image filter is the process of removing various types of noise from the images. The ensuant image is an information rich image than the original input image. The filtering finds its application in many fields from medical imagery, face detection, robot navigation, object detection, aircraft maintenance to image enhancement and image restoration. In the field of medical sciences the filter serves the purpose of image enhancement for efficient disease diagnosis, in aircraft maintenance for the purpose of detection of faults during takeoff, in case of face detection, object recognition and robot navigation used for object detection. This paper uses different quantitative metrics to analyze the result of different filtering techniques on an image. Initially, well known registered images from various aspects of science and nature are taken such as one image ct. jpg from medical sciences, two images Lighthouse. jpg, Penguins. jpg of natural scenery, two images of faces Koala. jpg, lena. jpg and a picture of naturally grown flowers Tulips. jpg are taken as input. Filtering techniques namely Median Filter (MF), Adaptive Filter (AF), New Adaptive Median Filer (NAMF), New Adaptive Spatial Filter (NASF), Edge Preserving Smooth Filter (EPSF) are applied on them. Further the filtered images are analyzed using five quantitative metrics such as Entropy (EN), Standard Deviation (SD), Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), and Mean Absolute Error (MAE). From the experimental result and the corresponding metrics used we observed that the resultant image is more informative than the original source images.

References
  1. Sanjay Singh , Chauhan R. P. S, Devendra Singh "Comparative Study of Image Enhancement using Median and High Pass Filter-ing Methods", Journal of Information and Operations Management, vol. 3,pp. 96-98, 2012.
  2. Muhammad Mizanur Rahman, Faisal Ahmed, Mohammed Imrul JubairSyed Ashfaqueuddin Priom, Imtiaz Masud Ziko "An Enhanced Non-Linear Adaptive Filteing Technique for Removing High Density Salt-and-Pepper Noise", International Journal of Computer Applications, vol. 38, no. 11, pp. 7-12, January 2012.
  3. Punyaban Patel, Banshidhar Majhi, Abhishek Tripathi, C. R. Tripathy, "A New Adaptive Median Filtering Technique for Removal of Impulse Noise from Images", ICCCS'11, pp. 462-467, February 2011.
  4. Amiya Halder, Sandeep Shekhar, Shashi Kant, Musheer Ahmed Mubarki, Anand Pandey "A New Efficient Adaptive Spatial Filter for Image Enhancement", Second International Conference on Computer Engineering and Applications, pp. 244-246, 2010.
  5. Shawn Chen, Tian-Yuan Shih, "On the evaluation of edge preserving smoothing filter, In Proceeding Geoinformatics, p. p C43, 2002.
  6. S. Rajkumar, S. Kavitha, " Redundancy Discrete Wavelet Transform and Contourlet Transform for Multimodality Medical Image Fusion with fQuantitative Analysis", 3rd International Conference on Emerging Trends in Engineering and Technology, November 2010.
  7. Shuyue Chen, Yun Qiu, Jun Feng, "A Nonlinear Filter Based on Row and Column Operation for Positive Impulsive Noise Reduction", Asia-Pacific Conference on Information Processing, pp. 44-46, 2009.
  8. Zhou Dengwen and Shen Xiaoliu, "Image Denoising Using Weighted Averaging", International Conference on Communications and Mobile Computing, pp. 400-403, 2009.
  9. Banshidhar Majhi," Soft Computing Techniques for Image Restoration", PhD Thesis, Sambalpur University, 2003.
  10. Krishan Kant Lavania, Shivali, Rajiv Kumar, " Image Enhancement using Filtering Techniques", International Journal of Computer Science and Engineering, vol. 4, pp. 14-20, January 2012.
  11. A. K. Jain, "Fundamentals of digital image processing", Prentice-Hall of India,1989
  12. Gonzalea R. C, Woods R. E. , "Digital Image Processing", 3rd edition, Pearson Education, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Image Enhancement Salt and Pepper noise Gaussian noise Quantitative Analysis