Research Article
Panchromatic and Multispectral Image Registration and Fusion for High Spatial and Spectral Information by Minimizing Registration Error
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 178 - Issue 6 |
| Published: Nov 2017 |
| Authors: Shashidhar Sonnad, Lalitha Y. S., Malvika Pujari |
10.5120/ijca2017915830
|
Shashidhar Sonnad, Lalitha Y. S., Malvika Pujari . Panchromatic and Multispectral Image Registration and Fusion for High Spatial and Spectral Information by Minimizing Registration Error. International Journal of Computer Applications. 178, 6 (Nov 2017), 10-13. DOI=10.5120/ijca2017915830
@article{ 10.5120/ijca2017915830,
author = { Shashidhar Sonnad,Lalitha Y. S.,Malvika Pujari },
title = { Panchromatic and Multispectral Image Registration and Fusion for High Spatial and Spectral Information by Minimizing Registration Error },
journal = { International Journal of Computer Applications },
year = { 2017 },
volume = { 178 },
number = { 6 },
pages = { 10-13 },
doi = { 10.5120/ijca2017915830 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2017
%A Shashidhar Sonnad
%A Lalitha Y. S.
%A Malvika Pujari
%T Panchromatic and Multispectral Image Registration and Fusion for High Spatial and Spectral Information by Minimizing Registration Error%T
%J International Journal of Computer Applications
%V 178
%N 6
%P 10-13
%R 10.5120/ijca2017915830
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Image fusion is a process of combining data from multiple images of a single object or same scene to produce an image which retains information from either of the images. The fusion of satellite images will unite PAN and MS images to generate new MS image having the qualities of both the input images. The registration process is to align both the images. Proper registration of panchromatic and multispectral images produces the good fusion result. Proposed Novel Registration and Fusion method uses, Speeded Up Robust Feature (SURF) method with Random Sample Consensus algorithm to combine the PAN and MS images. Eight performance measurement parameters are considered to validate the fusion result.
References
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