원문정보
보안공학연구지원센터(IJSIP)
International Journal of Signal Processing, Image Processing and Pattern Recognition
Vol.8 No.12
2015.12
pp.181-194
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
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
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
저자정보
참고문헌
자료제공 : 네이버학술정보