SURF-based registration for hyperspectral images

Experimental results related to the paper SURF-based registration for hyperspectral images by Álvaro Ordóñez, Dora B. Heras, and Francisco Argüello, published in the proceedings of the 2019 International Geoscience and Remote Sensing Symposium.

The alignment of images, also known as registration, is a relevant task in the processing of hyperspectral images. Among the feature-based registration methods, Speeded Up Robust Features (SURF) has been proposed as a computationally efficient approach. In this paper HSI-SURF is proposed. This is a method to register hyperspectral remote sensing images based on SURF that takes advantage of the full spectral information of the images. In this sense, the proposed method selects specific bands of the images and adapts the keypoint descriptor and the matching stages to benefit from the spectral information, thus increasing the effectiveness of the registration.

Compiled program to register two hyperspectral images.

• HSI-SURF algorithm: hsisurf.zip

All images used in the paper are available in Registration Repository

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