A new hybrid spectral similarity measure for discrimination of Vigna species

TL;DR

This paper introduces a novel hybrid spectral similarity measure combining spectral correlation angle and spectral information divergence, improving discrimination of Vigna species in hyperspectral data.

Contribution

A new hybrid spectral similarity measure is proposed, enhancing species discrimination accuracy over existing methods by integrating spectral correlation angle with spectral information divergence.

Findings

Proposed method outperforms existing hybrid approaches in spectral discrimination.

Higher relative discriminatory power in 400-700nm spectral region.

Experimental validation with laboratory spectra confirms improved accuracy.

Abstract

The reflectance spectrum of the species in a hyperspectral data can be modelled as an n-dimensional vector. The spectral angle mapper computes the angle between the vectors which is used to discriminate the species. The spectral information divergence models the data as a probability distribution so that the spectral variability between the bands can be extracted using the stochastic measures. The hybrid approach of spectral angle mapper and spectral information divergence is found to be better discriminator than spectral angle mapper or spectral information divergence alone. The spectral correlation angle is computed as a cosine of the angle of the Pearsonian correlation coefficient between the vectors. The spectral correlation angle is a better measure than the spectral angle mapper as it considers only standardized values of the vectors rather than the absolute values of the vector. In the present paper a new hybrid measure is proposed which is based on the spectral correlation angle and the spectral information divergence. The proposed method has been compared with the hybrid approach of spectral information divergence and spectral angle mapper for discrimination of crops belonging to Vigna species using measures like relative spectral discriminatory power, relative discriminatory probability and relative discriminatory entropy in different spectral regions. Experimental results using the laboratory spectra show that the proposed method gives higher relative discriminatory power in 400nm-700nm spectral region.