High spatial resolution hyperspectral image using fusion technique

Abstract

Now a day's remote sensing imaging is extensively used in the study of land resources, surface geology, water resources, landslide study, forest study, urban development at large scale. Always there is a need to improve the spatial and spectral information of remote sensing data. This can be done either by building new satellites with high resolution power or by using image processing techniques. Building a new satellite with high power is much more expensive, so it is an advantage of using image processing techniques. Hyperspectral imaging sensor provides better spectral resolution, but provide poor spatial resolution and multispectral imaging sensor provides good spatial resolution but provide poor spectral resolution. There are many fusion techniques such as Gram Schmidt Pan Sharpening, Principal Component Transform, High Pass Filtering are used to sharpen Multispectral Image with panchromatic image. To sharpen the hyperspectral image we are trying to fuse the HSI with MSI with the existing techniques and are quantified using Mean Square Error, Peak Signal to Noise Ratio, Entropy, and Universal Image Quality Index.