Assessment Protocols and Comparison of Ordering Relations for Spectral Image Processing

Abstract

Recent developments in hyperspectral sensors allow us to obtain high spectral and spatial resolutions that are close to the optical and physical structures of acquired surfaces. Consequently, hyperspectral imaging is used for its potential gain of accuracy. To preserve this metrological potential, generated bias, errors, and uncertainties must be managed at all subsequent processing levels. Based on the argument that a spectral image processing should avoid the linear approach, this paper proposes several protocols for assessing the quality of spectral ordering relations. The protocols include considerations of theoretical properties to ensure result stability, in physical aspects of spectral processing to ensure the link to physical properties of materials, and experimental results using spectral images with physical ground truth to assess bias and errors. Full-band ordering relations are compared in order to find that which satisfies all of the expected properties of a metrological spectral image processing.