Fusion: Practice and Applications
  FPA
  2692-4048
  2770-0070
  
   10.54216/FPA
   https://www.americaspg.com/journals/show/4160
  
 
 
  
   2018
  
  
   2018
  
 
 
  
   Pan-Sharpening Landsat Images through the Component Substitution Methods
  
  
   Department of Computer, College of Science, University of Mustansiriyah, Baghdad, Iraq
   
    Asmaa
    Asmaa
   
  
  
   Remotely sensed images have played a valuable role in several applications such as image classification, feature extraction, land cover monitoring, and others; thus, the need for high-resolution satellite images has become necessary and essential. In order to produce images with very high spectral and spatial resolution, the pan-sharpening techniques—, which are regarded as a subset of data fusion techniques—combine the color information of the multispectral image from the same scene with the distinct geometric features of the panchromatic image. This work conducts a comparative analysis of four pansharpening methods (Gram, HIS, Brovey, and PC) specifically applied to Landsat 7 images, providing a thorough evaluation across multiple performance metrics. Also we introduce and apply performance metrics that not only measure quantitative accuracy (like RMSE and RASE) but also assess the preservation of spatial details, offering a more holistic evaluation of pansharpening techniques. The qualitative and quantitative results indicate that both GS and IHS techniques have accurate performance.
  
  
   2026
  
  
   2026
  
  
   336
   343
  
  
   10.54216/FPA.210123
   https://www.americaspg.com/articleinfo/3/show/4160