Survey of Different Fusion Techniques and Quality Metric Assessment for Remote Sensing Image Fusion

Abstract

Remote sensing image fusion plays a vital role in the applications of remote sense such as the inference of agricultural products and water wealth. Image fusion technique is referred as the combination of more images into single image to get detail and accurate information. Image fusion aims at civilizing spectral and spatial data in fused image. To get both information, different fusing techniques are used. In our algorithm, we recommend a survey of different fusion models like, Intensity Hue Saturation (IHS), Brovey, Principal Component Analysis(PCA), Guided and Non sub sampled contourlet transform (NSCT) for remote sensing image fusion.