ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774

A LIGHTWEIGHT CNN ARCHITECTURE FOR LANDCLASSIFICATION ON SATELLITE IMAGES

Abstract

Abstract: Image matching is a fundamental method for gathering 1 ground control points (GCPs) by establishing a link betweenincoming images and reference image map chips. It is a required step in the automatic precise geo-registration of satellite images.To increase georeferencing accuracy, reference chips on the photographs must be properly aligned. With a limited supply of chips,the need for a higher matching success rate rises. This study compares incoming satellite photographs to reference chips derivedfrom aerial colour ortho-images. It is difficult to match the two datasets since they have different spectral responses and textures. Toimprove the matching success rate, we employ pan-sharpened satellite pictures. The results revealed a greater matching success ratewith pansharpened images due to the similar spectral spectrum and enhanced spatial resolution. As a consequence, pansharpenedpictures may help to improve picture matching success rates in automatic accurate georeferencing of high-resolution satellitephotographs

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