Band selection algorithm for orb feature detector in hyperspectral earth remote sensing data

by

G.R. Kasoev, G.A. Scherbina

Moscow Institute of Physics and Technology,

RF, Moscow, Kerchenskaya St., 28A

DOI: 10.33075/2220-5861-2024-2-95-103

UDC 004.93’11                                                          

EDN: https://elibrary.ru/lohjao

Abstract:

ORB feature detector is used for stitching of images from different optical channels of two-slit hyperspectrometer. It is essential to choose a subset of all available spectral bands to avoid computational complexity. Two band selection algorithms are discussed in the scope of this work. Algorithms are spectral cluster center search (ECA) and estimation of information sufficiency and redundancy based on pairwise correlation (BCA). Algorithms are modified with spectral distance between bands to ensure search for spectrally robust features. Testing with EO-1 Hyperion data is conducted. Results show that modification increases the number of detected feature and accuracy of matched pairs by 10-20% for ECA algorithm without substantially increasing computational time.

Keywords: hyperspectrometer, feature, ORB, image stitching, ECA, BCA.

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