Atmospheric blur is the distortion of image due to long time exposure, fog, wind speed and due to randomly change in refractive index of air through which light travels. Atmospheric blur also occur through non-uniform geometric deformation of image. In this article, we propose a method for restoring atmospheric degraded image using artificial neural network. In proposed methodology use multilayer feed-forward network which trained by error back propagation algorithm and randomly initialize weights of network. This technique provides better result to restore atmospheric blur image and also in the presence of noise.
목차
Abstract 1. Introduction 2. Back Propagation Algorithm 3. Neural Network Model Features A. Activation Function B. Hidden Layers and Nodes c. Stopping Criterion D. Momentum Factor 4. Proposed Methodology 5. Result Analysis 6. Conclusion and Future Scope References
키워드
Back PropagationANN (Artificial Neural Network)atmospheric turbulencePSNR (Peak Signal to Noise Ratio)
저자
Azad Singh [ Department of Computer Science Engineering and Information Technology Madhav Institute of Technology & Science Gwalior, India ]
Rajeev Kumar Singh [ Department of Computer Science Engineering and Information Technology Madhav Institute of Technology & Science Gwalior, India ]
보안공학연구지원센터(IJSIP) [Science & Engineering Research Support Center, Republic of Korea(IJSIP)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Signal Processing, Image Processing and Pattern Recognition
간기
격월간
pISSN
2005-4254
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.8 No.12