Description

Pan-sharpening is a common post processing operation for captured multispectral satellite imagery, where the spatial resolution of images gathered in various spectral bands is enhanced by fusing them with a panchromatic image captured at a higher resolution. In this paper, pan-sharpening is formulated as the problem of jointly estimating the high-resolution (HR) multispectral images to minimize an objective function comprised of the sum of squared residual errors in physically motivated observation models of the low-resolution (LR) multispectral and the HR panchromatic images and a correlation-dependent regularization term. In our proposed we use Low pass filter to find the error in LR image and using the iterative method to join the LR and HR image with low SNR value.