An assessment of pyramid-based multisensor image data fusion

This paper reports about a quantitative evaluation of pyramid-based schemes performing a feature-based fusion of data from multispectral and panchromatic imaging sensors having different ground,resolutions. A critical point is performances evaluation of image data fusion. A set of quantitative parameters has been recently proposed. Both visual quality, regarded as contrast, presence of fine details, and absence of impairments and artifacts (e.g., blur, ringing), and spectral fidelity (i.e., preservation of spectral signatures) are concerned and embodied in the measurements. The aim of the present work is to provide a comprehensive performance comparison on SPOT data among three feature-based schemes for image fusion, as well as on a specific case study on which multisensor observations were available. Out of the three methods compared respectively based on high-pass filtering (HPF), wavelet transform (WT), and generalized Laplacian pyramid (GLP), the fatter two are far more efficient than the former, thus establishing the advantages for data fusion of a formally multiresolution analysis.