NDLI: Objective Evaluating Method to Fusion Image Quality Based on ANN

Content Provider	IEEE Xplore Digital Library
Author	Zhang Yong Zhang Ling
Copyright Year	2010
Abstract	Research on quality evaluating of fusion images is meaningful to improve the registration technology and fusion algorithms. The objective assessment metrics based on fusion image itself can not show comprehensively the fusion image quality, which could be incongruent against human eye response. Provide a new assessment method for fusion image quality by means of building artificial neural network model. The metrics inculding mean value, standard deviation, gradient is choosed as the input neural cell. A hidden layer is designed to carry out assorting perfoemance. And the artificial neural network obtain the image quality assessing mapping functions and to classify the training samples into different types by means of the supervised learning. The experiment shows the noteworthy concordance between the simulation result and human eye response to identifying samples. Compared with single evaluation indexes, the new quality evaluation model can show effectively the subjective response of human eye to fusion image.
Starting Page	291
Ending Page	294
File Size	2771291
Page Count	4
File Format	PDF
ISBN	9781424476695
e-ISBN	9781424476701
DOI	10.1109/ISME.2010.112
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Measurement Image quality Evaluation Fusion image Artificial neural networks Artificial neural net Entropy Equations Testing
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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