Multilevel Quantum Inspired Fractional Order Ant Colony Optimization for Automatic Clustering of Hyperspectral Images
- Title
- Multilevel Quantum Inspired Fractional Order Ant Colony Optimization for Automatic Clustering of Hyperspectral Images
- Creator
- Bhattacharyya S.; Dutta T.; Dey S.
- Description
- Hyperspectral images contain a wide variety of information, varying from relatively large regions to smaller manmade buildings, roads and others. Automatic clustering of various regions in such images is a tedious task. A multilevel quantum inspired fractional order ant colony optimization algorithm is proposed in this paper for automatic clustering of hyperspectral images. Application of fractional order pheromone updation technique in the proposed algorithm produces more accurate results. Moreover, the quantum inspired version of the algorithm produces results faster than its classical counterpart. A new band fusion technique, applying principal component analysis and adaptive subspace decomposition, is successfully proposed for the pre-processing of hyperspectral images. Score Function is used as the fitness function and K-Harmonic Means is used to determine the clusters. The proposed algorithm is implemented on the Xuzhou HYSPEX dataset and compared with classical Ant Colony Optimization and fractional order Ant Colony Optimization algorithms. Furthermore, the performance of each method is validated by peak signal-to-noise ratio which clearly indicates better segmentation in the proposed algorithm. The Kruskal-Wallis test is also conducted along with box plot, which establishes that the proposed algorithm performs better when compared with other algorithms. 2020 IEEE.
- Source
- 2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings
- Date
- 2020-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Fractional Order Ant Colony Optimization; Hyperspectral Image Segmentation; Kruskal-Wallis test; Peak signal-to-noise ratio; Qutrits
- Coverage
- Bhattacharyya S., Christ (Deemed to Be University), Department of Computer Science Engineering, Bangalore, Karnataka, India; Dutta T., University Institute of Technology, Burdwan University, Department of Computer Science Engineering, West Bengal, India; Dey S., Sukanta Mahavidyalaya Dhupguri, Department of Computer Science, Jalpaiguri, West Bengal, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-172816929-3
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Bhattacharyya S.; Dutta T.; Dey S., “Multilevel Quantum Inspired Fractional Order Ant Colony Optimization for Automatic Clustering of Hyperspectral Images,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/20698.