A review on Hyperspectral Image Classification using SVM combined with Guided Filter

The classification of hyperspectral remote detecting picture is testing assignment in present time. In this survey hyperspectral picture characterization utilizing SVM joined with the guided filter to get the spatial data viably and de-commotion the grouping result by edge-preserving smoothing property. In the paper [1], spatial data for hyperspectral picture classification gathered using morphological profile and local binary pattern. To, begin with, image classifier is utilized to group every pixel and after that apply the guided filter for edge-smoothing property otherwise called edge-preserving filtering(EPF) to the outcome which is utilized to enhance classification exactness. When it is contrasted with existing customary classification techniques, it may provide better classification exactness. It will be beneficial for future remote-detecting image classification.