Exploring the MSER-based hyperspectral remote sensing image registration

Álvaro Ordóñez; Dora B. Heras; Francisco Argüello

doi:10.1117/12.2574200

20 September 2020 Exploring the MSER-based hyperspectral remote sensing image registration

Álvaro Ordóñez, Dora B. Heras, Francisco Argüello

Proceedings Volume 11533, Image and Signal Processing for Remote Sensing XXVI; 115330E (2020) https://doi.org/10.1117/12.2574200
Event: SPIE Remote Sensing, 2020, Online Only

Abstract

Image registration is an essential preprocessing task in many applications of hyperspectral images capturing the Earth surface. Maximally Stable Extremal Regions (MSER) is a feature–based method for image registration which extracts regions by thresholding the image at different grey levels. Its invariance to affine transformations makes it ideal for image registration. This method is usually employed in text detection and recognition as well as in the medical domain. Hyperspectral images contain spectral information that can be used for improving the image alignment. This article presents a first approach to a hyperspectral remote sensing image registration method based on MSER that efficiently exploits the information contained in the different spectral bands. The experimental results over four hyperspectral images show that the proposed method is promising as it achieves a higher number of correct registration cases than other feature–based methods.

Conference Presentation

Citation Download Citation

Álvaro Ordóñez, Dora B. Heras, and Francisco Argüello "Exploring the MSER-based hyperspectral remote sensing image registration", Proc. SPIE 11533, Image and Signal Processing for Remote Sensing XXVI, 115330E (20 September 2020); https://doi.org/10.1117/12.2574200

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