Paper Info
Title
A neural network method for image resolution enhancement from a multiple of image frames
Abstract
This paper presents a neural network based method to estimate a high resolution image from a sequence of low resolution image frames. In this method, a multiple of layered feed-forward neural networks is specially designed to learn an optimal mapping from a multiple of low resolution image frames to a high resolution image through training. Simulation results demonstrate that the proposed neural networks can successfully learn the mapping in the presented examples and show a good potential in solving image resolution enhancement problem, as it can adapt itself to the various changeable conditions. Furthermore, due to the inherent parallel computing structure of neural network, this method can be applied for real-time application, alleviating the computational bottlenecks associated with other methods and providing a more powerful tool for image resolution enhancement.
Year
DOI
Venue
2011
10.1007/978-3-642-21111-9_22
ISNN (3)
Keywords
Field
DocType
good potential,neural network,image resolution enhancement,high resolution image,layered feed-forward neural network,neural network method,optimal mapping,computational bottleneck,proposed neural network,image resolution enhancement problem,low resolution image frame,parallel computer,low resolution,image resolution,feed forward neural network
Computer vision,Pattern recognition,Feature detection (computer vision),Computer science,Sub-pixel resolution,Artificial intelligence,Artificial neural network,Image resolution,Multiple,Machine learning
Conference
Volume
ISSN
Citations 
6677
0302-9743
0
PageRank 
References 
Authors
0.34
6
2
Name
Order
Citations
PageRank
Shuangteng Zhang1182.85
Ezzatollah Salari27112.58