Hybrid fusion approach for synthetic aperture radar and multispectral imagery for improvement in land use land cover classification

摘要: Multisensor image fusion has gained tremendous significance due to various satellites operating in different parts of the electromagnetic spectrum. We present a hybrid approach integrate information from synthetic aperture radar (SAR) and multispectral (MS) imagery improve land use cover (LULC) classification. The major concern SAR optical is spectral distortion fused image, which significantly less pansharpening algorithms. primary objective our work inject unique spatial into MS images, deriving enhanced data. proposed based on integration principal component analysis wavelet decomposition reduce image. Fused images are evaluated visually statistically. Results compared with conventional approaches. In order explore effectiveness technique, LULC classification performed original results analytically standard thematic map derive accuracy. A comparative other approaches conclusively proves that superior