Aggrandized Aspect Based Mosaicing Technique for Scientifically Stigmatized Airborne Synthetic Aperture Radar
Keywords:
Mosaicing Technique, Synthetic Aperture Radar, RANSAC, KAZE, SAR, SHIFT algorithmAbstract
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.
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