期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2021
卷号：12
期号：9
DOI：10.14569/IJACSA.2021.0120923
语种：English
出版社：Science and Information Society (SAI)
摘要：Remote sensing images with high spatial and temporal resolution (HSHT) for GIS land use monitoring are crucial data sources. When trying to get HSHT resolution images, cloud cover is a typical problem. The effects of cloud cover reduction using the ESTARFM, one of spatiotemporal image fusion technique, is examined in this study. By merging two satellite photos of low-resolution and medium-resolution images, the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Method (ESTARFM), predicts the reflectance value of the cloud cover region. ESTARFM, on the other hand, employs both medium and high-resolution satellite pictures in this study. Using Sentinel 2 and Landsat 8, the Peak Signal Noise Ratio (PSNR) statistical methods are then utilized to evaluate the ESTARFM. The PSNR explain ESTARFM cloud removal performance by comparing the level of similarity of the reference image with the reconstructed image. In remote sensing, this hypothesis was established to get high-quality HSHT pictures. Based on this study, Landsat 8 images that have been cloud removed with ESTARFM may be classed as good. The PSNR value of 21.8 to 26 backs this up, and the ESTARFM result seems good on visual examination.
关键词：Cloud removal; RS-Remote sensing; PSNR-Peak signal noise ratio; GIS-Geographic information system; spatiotemporal image fusion
