MTF-Adjusted Pansharpening Approach Based on Coupled Multiresolution Decompositions

Among others, the wavelet-based pansharpening approach tries to enhance the resolution of the multispectral (MS) image by injection of spatial details extracted from the high-resolution panchromatic (PAN) image. The problem is presented as follows, the inputs are a coarse-resolution MS image and a high-resolution detail image provided from the PAN image; therefore, one would think that the wavelet reconstruction allows combining approximations and details to construct the high-resolution MS image. However, the wavelet transform (WT) assumes that details and approximations are calculated using the same wavelet decomposition. Now, in the pansharpening case, the MS low-resolution image is assumed to be aliased and blurred due to the imaging system modulation transfer function (MTF) that is approximated as a specific low-pass filter. Meanwhile, there are no constraints about details that can be extracted from PAN using discrete WT (DWT). Approximation and details are not any more orthogonal as needed in the reconstruct of the MS high-resolution image based on DWT. For that, we propose in this paper a new fusion schema [coupled multiresolution decomposition model (CMD)] allowing the reconstruction of a high-resolution MS given its approximation and details obtained by MTF-tailored downsampling and wavelet decomposition, respectively. For validation, CMD is applied to Pléiades, GeoEye-1, and SPOT 6 images. Compared to other approaches [i.e., Gram-Schmidt (GS) adaptive, GS mode 2 (GS2), “À trous´ WT (AWT), generalized Laplacian pyramid (GLP), DWT, and PCI Geomatics software algorithm], our method performs generally better.