| Title | Nearest Neighbor Search In Hyperspectral Data Using Binary Space Partitioning Trees |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Myasnikov, Evgeny |
| Conference Name | 2021 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) |
| Keywords | Atmospheric measurements, ball-tree, Bhattacharyya Angle, binary space partitioning trees, data structures, Euclidean distance, Force, hellinger distance, Measurement, Metrics, Nearest neighbor methods, nearest neighbor search, Particle measurements, pubcrawl, Signal processing algorithms, Spectral Angle Mapper, Spectral Information Divergence, vp-tree |
| Abstract | Fast search of hyperspectral data is crucial in many practical applications ranging from classification to finding duplicate fragments in images. In this paper, we evaluate two space partitioning data structures in the task of searching hyperspectral data. In particular, we consider vp-trees and ball-trees, study several tree construction algorithms, and compare these structures with the brute force approach. In addition, we evaluate vp-trees and ball-trees with four similarity measures, namely, Euclidean Distance, Spectral Angle Mapper Bhattacharyya Angle, and Hellinger distance. |
| DOI | 10.1109/WHISPERS52202.2021.9484041 |
| Citation Key | myasnikov_nearest_2021 |
Nearest Neighbor Search In Hyperspectral Data Using Binary Space Partitioning Trees