Pan-sharpening: Use of difference of Gaussians

In this paper, we propose a fast method for pan-sharpening based on difference of Gaussians (DoGs). The Panchromatic (Pan) and the multi-spectral (MS) images are used to obtain a pan-sharpened image having both high spectral and spatial resolutions. The method is based on two level DoG on the Pan image. First, the Pan image is convolved with Gaussian kernel to obtain a blurred version and the high frequency details are extracted as the first level DoGs by subtracting the blurred image from the original. In order to get the second level DoG, same steps are repeated on the blurred Pan image. The extracted details at both DoGs are added to MS image to obtain the final pan-sharpened image. Experiments have been conducted with different values of standard deviation of Gaussian blur with images captured from different satellite sensors such as Ikonos-2, Quickbird and Worlview-2. A relatively new quality measure with no reference (QNR) index along with the other traditional measures are evaluated to check the efficacy of the proposed algorithm. The subjective and the quantitative assessment show that the proposed technique performs better, fast and less complex when compared to recently proposed state of the art techniques.