MTF-deblurring preprocessing for CS and MRA pansharpening methods

The fusion of low resolution multispectral (MS) images and high resolution panchromatic (PAN) images, i.e., pansharpening, is an important technique in remote sensing and has many applications where high resolution imagery is important. Component substitution (CS) and multiresolution analysis (MRA) are two large families of pansharpening methods that are fast and computationally efficient. They can be described using a general framework, where details from the PAN image are added to the upsampled and interpolated MS image. However, these methods often suffer from spectral and spatial distortions. We propose a pre-processing step, where instead of just interpolating the MS image to the resolution scale of the PAN image, we do a deconvolution of the interpolated MS image based on the sensor´s modulation transfer function (MTF). This results in large improvement gains in the spectral and spatial quality of the fused image. We demonstrate our method using a real WorldView-2 dataset and show that our approach significantly improves the tested methods in both the CS and MRA families of pansharpening methods.