Earticle

초록

영어

Various kinds of images and pictures are required as sources of information for analysis and interpretation. When an image is converted from one form to another such as scanning, transmitting, digitizing, storing etc., degradation occurs to the output image. Hence, the output image needs to be enhanced in order to be better analyzed. Denoising is the one of the pre processing technique in digital image processing. This paper investigates the performance of four denoising methods for removing the High Density Impulse Noise. They are Adaptive Bilateral Filter (ABF), Fuzzy Peer Group Filter (FPGF), Switching Bilateral Filter (SBF), and Boundary Discriminative Noise Detection Filter (BDND).The performance of the above four filters is compared by using five performance metrics. They are Peak-Signal-to-Noise-Ratio, Mean Square Error and Root Mean Square Error. The Experimental results show that the BDND filter based denoising method performs well than the other three methods.

목차

Abstract
 1. Introduction
 2. Algorithm
  2.1. Adaptive Bilateral Filter [11]
  2.2. Fuzzy Peer Group Filter [12]
  2.3. Switching Bilateral Filter [13]
  2.4 BDND Filter [14]
 3. Experiments & Results
  3.1. Experimental Images:
  3.2. Performance Metrics:
  3.3. Performance Analysis:
 4. Conclusion
 References

키워드

저자

• V. Murugan [ Research Scholar, Department of Computer Science & Engg, Manonmaniam Sundaranar University, Tirunelveli – 627012, TamilNadu, India. ]
• T. Avudaiappan [ Research Scholar, Department of Computer Science & Engg, Manonmaniam Sundaranar University, Tirunelveli – 627012, TamilNadu, India. ]
• Dr. R. Balasubramanian [ Professor, Department of Computer Science & Engg, Manonmaniam Sundaranar University, Tirunelveli – 627012, TamilNadu, India. ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605