Weighted Sum of Segmented Correlation: an Efficient Method for Spectra Matching in Hyperspectral Images
Document Type
Conference Article
Publication Title
International Geoscience and Remote Sensing Symposium IGARSS
Abstract
Matching a target spectrum with known spectra in a spectral library is a common method for material identification in hyperspectral imaging research. Hyperspectral spectra exhibit precise absorption features across different wavelength segments, and the unique shapes and positions of these absorptions create distinct spectral signatures for each material, aiding in their identification. Therefore, only the specific positions can be considered for material identification. This study introduces the Weighted Sum of Segmented Correlation method, which calculates correlation indices between various segments of a library and a test spectrum, and derives a matching index, favoring positive correlations and penalizing negative correlations using assigned weights. The effectiveness of this approach is evaluated for mineral identification in hyperspectral images from both Earth and Martian surfaces.
First Page
8015
Last Page
8018
DOI
10.1109/IGARSS53475.2024.10642546
Publication Date
1-1-2024
Recommended Citation
Soor, Sampriti; Kumari, Priyanka; Daya Sagar, B. S.; and Shetty, Amba, "Weighted Sum of Segmented Correlation: an Efficient Method for Spectra Matching in Hyperspectral Images" (2024). Conference Articles. 913.
https://digitalcommons.isical.ac.in/conf-articles/913