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IMAGE ANALYSIS AND SEGMENTATION
Comparing high spatial resolution image simplifications before a segmentation process
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accuracy algorithm analysis angle applied approach bands calculated classification clusters coefficients color compared component compression computed considered correlation corresponding defined dependent described detection developed distribution effect elements error estimation evaluation example experiments extraction field Figure filter frequency function fused fusion Gaussian given horizons hyperspectral IEEE improvement Italy labelled linear matching matrix mean measure method morphological multispectral noise objects observed obtained operations optimal original parameters pattern performed pixel possible present problem procedure processing properties proposed radar range reference reflectance regions Remote Sensing represent resolution respectively samples scale scene scheme segmentation selection sensor shadows shape shown shows signal space spatial spectral SPIE standard statistical step structure surface Table techniques texture threshold transform tree values vector vegetation wavelet