Kösesoy I.Tepecik A.Çetin M.Mesut A.2024-06-122024-06-1220129.78147E+12https://doi.org/10.1109/SIU.2012.6204511https://hdl.handle.net/20.500.14551/163292012 20th Signal Processing and Communications Applications Conference, SIU 2012 -- 18 April 2012 through 20 April 2012 -- Fethiye, Mugla -- 90786In literature, several methods are available to combine both low spatial multispectral and low spectral panchromatic resolution images to obtain a high resolution multispectral image. One of the most common problems encountered in these methods is spectral distortions introduced during the merging process. At the same time, the spectral quality of the image is the most important factor affecting the accuracy of the results in many applications such as object recognition, object extraction, image analysis. In this study, the most commonly used methods including GIHS, GIHSF, PCA and Wavelet are analyzed using image quality metrics such as SSIM, ERGAS and SAM. At the same time, Wavelet is the best method for obtaining the fused image having the least spectral distortions according to obtained results. At the same time, image quality of GIHS, GIHSF and PCA methods are close to each other, but spatial qualities of the fused image using the wavelet method are less than others. © 2012 IEEE.tr10.1109/SIU.2012.6204511info:eu-repo/semantics/closedAccessCommon Problems; Comparative Analysis; Fused Images; High Resolution; Image Fusion Methods; Image Quality Metrics; Merging Process; Multi-Spectral; Multispectral Images; Object Extraction; Pca Method; Resolution Images; Spatial Quality; Spectral Distortions; Spectral Quality; Wavelet Methods; Image Analysis; Image Fusion; Image Quality; Object Recognition; Signal Processing; Feature ExtractionConference Object2-s2.0-84863451246N/A