POTENTIAL EVALUATION OF DIFFERENT DATA FUSION TECHNIQUES IN REMOTE SENSING

Data fusion techniques have been widely used to process earth observation data on the ground, which can generate data with higher quality and extract better information from multi-source or multi-temporal data. However, a few comparison research works have been done in current literature to evaluate the quality of the fused image from different fusion methodologies. This study examines properties of fused images and their ability to preserve the spectral and intensity integrity of the original image. It analyzes eight current data fusion techniques as applied to a complex scene to assess their performance. In our evaluation, eight data fusion models used: one spatial domain model (High-Pass Filter), one algebraic models (Brovey Transform), two spectral domain models (Principal Components Transform and Intensity-Hue-Saturation), two Wavelet transform techniques, one morphological method, and one Laplacian Method.