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October 2022
Conference Paper
Title
From Hyperspectral to Multispectral Sensing and from Simulation to Reality: A Comprehensive Approach to Calibration Model Transfer
Abstract
High-resolution hyperspectral sensors provide precise but expensive information on an object’s chemical composition in various industries. We present a method for transferring this capability to customized low-cost multispectral solutions. Taking a relevance analysis of spectra for a given problem as our starting point, we simulated and designed a multispectral sensor based on inverse spectroscopy. The corresponding calibration model, which was derived from the simulation of such a multispectral sensor and connected with its hardware, may not drop in precision significantly. Different methods of calibration model transfer capable of handling a limited subset of the data were tested for this purpose. The latent space transformation with Chebyshev polynomials outperformed all other methods by yielding the fewest labeled data.
Author(s)
Open Access
File(s)
Rights
CC BY-ND 4.0: Creative Commons Attribution-NoDerivatives
Language
English