ACRS2015_3.pdf

ABSTRACT: The aim of this study is to evaluate the performances of different image fusion techniques for the enhancement of spectral and textural variations of different forest types using optical and microwave data sets. For the data fusion, modified intensity-hue-saturation (IHS) transformation, principal components analysis (PCA) method, Gram-Schmidt fusion, and wavelet-based method are used and the results are compared. Of these methods, the better results are obtained through the use of the modified IHS transformation and wavelet-based fusion. Overall, the research indicates that multisource data fusion can significantly improve the interpretation and analysis of variety of forest types.