HSI-MSER: Hyperspectral Image Registration Algorithm based on MSER and SIFT

Image alignment is an essential task in many applications of hyperspectral remote sensing images. Before any processing, the images must be registered. The Maximally Stable Extremal Regions (MSER) a feature detection algorithm that extracts regions by thresholding image at different grey levels. These extremal are invariant to transformations making them ideal for registration. Scale-Invariant Feature Transform (SIFT) well-known keypoint detector and descriptor based on construction Gaussian scale-space. This article presents registration method MSER SIFT description. It efficiently exploits information contained spectral bands improve alignment. experimental results over nine show proposed achieves higher number correct cases using less computational resources than other methods. Results evaluated terms accuracy also execution time.