Abstract
Thresholding of hyperspectral images is a tedious task. The interactive information value between three bands is used to reduce the redundant bands in the pre-processing stage. A qutrit-inspired genetic algorithm is proposed for thresholding the minimized hyperspectral images with improved quantum genetic operators. In this paper, a quantum disaster operation is implemented to rescue the qutrit-inspired genetic algorithm from getting stuck into local optima. The proposed algorithm produces better results than classical genetic algorithm and qubit-inspired genetic algorithm in most of the cases.
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Acknowledgements
This work was supported by the AICTE sponsored RPS project on Automatic Clustering of Satellite Imagery using Quantum-Inspired Metaheuristics vide F.No 8-42/RIFD/RPS/Policy-1/2017-18.
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Dutta, T., Dey, S., Bhattacharyya, S., Mukhopadhyay, S. (2021). Qutrit-Based Genetic Algorithm for Hyperspectral Image Thresholding. In: Bhattacharyya, S., Mršić, L., Brkljačić, M., Kureethara, J.V., Koeppen, M. (eds) Recent Trends in Signal and Image Processing. ISSIP 2020. Advances in Intelligent Systems and Computing, vol 1333. Springer, Singapore. https://doi.org/10.1007/978-981-33-6966-5_3
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DOI: https://doi.org/10.1007/978-981-33-6966-5_3
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