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Aggrandized Aspect Based Mosaicing Technique for Scientifically Stigmatized Airborne Synthetic Aperture Radar
Authors(2) :-D. Bhavya Lakshmi, Prof. N. Sathianandam
In the digital image processing, enhancement and removing the noise in the airborne synthetic aperture radar (SAR) image is a critical issue. We have proposed a Kaze algorithm to enhance radar image interpretation and the computational time are reduced by using the Adaptive Random Sample theory which limits the search space and work well for feature detection of synthetic aperture radar image(SAR).The performance of the proposed approach has been evaluated and compared to the existing technique, The statistics obtained from each randomly selected feature is used to update this distribution, by reducing the total required number of random trials. The re-estimation for those selected features are done within a smaller search space with a more accurate algorithm like the RANSAC fitting, thus the proposed technique show that this two-stage algorithm reduces the total computation time by limiting the search space. The entire algorithm is simple and effective. Thus the image interpretation is enhanced by invariant feature Point detector in the areas of computer vision, real time image matching and object recognition.
D. Bhavya Lakshmi, Prof. N. Sathianandam
Mosaicing Technique, Synthetic Aperture
Radar, RANSAC, KAZE, SAR, SHIFT algorithm
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Published in : Volume 2 | Issue 2 | March-April 2016
Date of Publication : 2016-04-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 286-291
Manuscript Number : IJSRST1622107
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
D. Bhavya Lakshmi, Prof. N. Sathianandam , "Aggrandized Aspect Based Mosaicing Technique for Scientifically Stigmatized Airborne Synthetic Aperture Radar", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 2, Issue 2, pp.286-291, March-April-2016
URL : http://ijsrst.com/IJSRST1622107