Sharpening Misrsat-1 data using Super-Resolution and HPF fusion methods

Spatial resolution enhancement is usually required in the remote sensing field. Super-Resolution (SR) is a fusion process for reconstructing a High-Resolution (HR) image from several Low-Resolution (LR) images covering the same region in the world. It is difficult, however, for some satellite remote sensing arrangements to get several images of the same scene in a short time, especially for highly dynamic scenes. In this paper, we study the SR process of Misrsat-1 data using sub-pixel shifts between bands 1, 3, and the Panchromatic (PAN) sub-band. Due to the difference in radiometry between the different bands, we propose performing the SR process between the high-pass details extracted from bands 1, 3, and the PAN, and then using the High-Pass Filter (HPF) fusion method for sharpening the Multi-Spectral (MS) image of Misrsat-1 using the super-resolved high-pass details. The comparison of the proposed method with the cubic convolution interpolation method has shown an enhancement in the image entropy, Point Spread Function (PSF), and Modulation Transfer Function (MTF).