Earticle

초록

영어

A class of neural filter for image enhancement is proposed in this paper. The proposed intelligent filter is carried out in two stages. In first stage the corrupted image is filtered by applying two special classes of decision based filters. Filtered image outputs from decision based filters are suitably combined with a Feed forward neural network in the second stage. The internal parameters of the feed forward neural network are adaptively optimized by training for three well known images. This is quite effective in eliminating impulse noise. Extensive simulation results show that the proposed filter is superior in terms of eliminating impulse noise as well as preserving edges and the results are compared with other existing filters.

목차

Abstract
 1. Introduction
 2. Noise Model
 3. Proposed Filter
  3.1. Decision based Switching Median Filter (DBSMF)
  3.2. Nonlinear Filter (NF)
  3.4. Feed forward Neural Network
  3.5. Training of the Feed Forward Neural Network
  3.6. Testing of Unknown Images using Trained Structure of Neural Network
  3.7. Filtering of the Noisy Image
 4. Results and Discussion
 5. Conclusion
 References

키워드

저자

• R.Pushpavalli [ Research Scholar, Electronics and Communication Engineering, Pondicherry Engineering College ]
• G.Sivarajde [ Professor, Electronics and Communication Engineering, Pondicherry Engineering College ]

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