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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/27671
Title: On sphering the high resolution satellite image using fixed point based ICA approach
Authors: Singh P.P.
Garg, Rahul D.
Kumar S.
Raman B.
Roy P.P.
Sen D.
Published in: Advances in Intelligent Systems and Computing
International Conference on Computer Vision and Image Processing, CVIP 2016
Abstract: On sphering the satellite data, classified images are achieved by many authors that had tried to reduce the mixing effect in image classes with the help of different Independent component analysis (ICA) based approaches. In these cases multispectral images are limited with small spectral variation in heterogeneous classes. For better classification, high spectral variance among different classes and low spectral variance within a particular class should exhibit. In the consideration of this issue, a Fixed point (FP) based Independent Component Analysis (ICA) method is utilized to get better classification accuracy in the existing mixed classes that consist similar spectral behavior. This FP-ICA method identifies the objects from mixed classes having similar spectral characteristics, on sphering high resolution satellite images (HRSI). It also helps to reduce the effect of similar spectral behavior between different image classes. The estimation of independent component related to non-gaussian distribution data (image) with optimizing the performance of this approach with the help of nonlinearity, which utilize the low variance between similar spectral classes. It is quite robust, effortless in computation and high convergence rate, even though the spectral distributions of satellite images are rigid to classify. Hence, this FP-ICA approach plays a key role in image classification such as buildings, grassland area, road, and vegetation. ¬© Springer Science+Business Media Singapore 2017.
Citation: Advances in Intelligent Systems and Computing (2017), 460 AISC: 411-419
URI: https://doi.org/10.1007/978-981-10-2107-7_37
http://repository.iitr.ac.in/handle/123456789/27671
Issue Date: 2017
Publisher: Springer Verlag
Keywords: Fixed point
Image classification
Independent component analysis
Mixed classes
Negentropy
Non-gaussianity
ISBN: 9789811021060
ISSN: 21945357
Author Scopus IDs: 57212591696
15044199700
Author Affiliations: Singh, P.P., Department of Computer Science & Engineering, Central Institute of Technology Kokrajhar, BTAD, Kokrajhar, Assam, India
Garg, R.D., Geomatics Engineering Group, Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India
Funding Details: 
Corresponding Author: Singh, P.P.; Department of Computer Science & Engineering, India; email: pankajp.singh@cit.ac.in
Appears in Collections:Conference Publications [CE]

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