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Landcover change detection using PSO-evaluated quantum CA approach on multi-temporal remote-sensing watershed images

Mahata, Kalyan ; Das, Rajib LU ; Das, Subhasish and Sarkar, Anasua LU (2018) 2. p.679-705
Abstract

Computer science plays a major role in image segmentation and image processing applications. Despite the computational cost, PSO evaluated QCA approaches perform comparable to or better than their crisp counterparts. This novel approach, proposed in this chapter, has been found to enhance the functionality of the CA rule base and thus enhance the established potentiality of the fuzzy-based segmentation domain with the help of quantum cellular automata. This new unsupervised method is able to detect clusters using 2-dimensional quantum cellular automata model based on PSO evaluation. As a discrete, dynamical system, cellular automaton explores uniformly interconnected cells with states. In the second phase, it utilizes a 2-dimensional... (More)

Computer science plays a major role in image segmentation and image processing applications. Despite the computational cost, PSO evaluated QCA approaches perform comparable to or better than their crisp counterparts. This novel approach, proposed in this chapter, has been found to enhance the functionality of the CA rule base and thus enhance the established potentiality of the fuzzy-based segmentation domain with the help of quantum cellular automata. This new unsupervised method is able to detect clusters using 2-dimensional quantum cellular automata model based on PSO evaluation. As a discrete, dynamical system, cellular automaton explores uniformly interconnected cells with states. In the second phase, it utilizes a 2-dimensional cellular automata to prioritize allocations of mixed pixels among overlapping land cover areas. The authors experiment on Tilaya Reservoir Catchment on Barakar River. The clustered regions are compared with well-known PSO, FCM, and k-means methods and also with the ground truth knowledge. The results show the superiority of the new method.

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author
; ; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Environmental Information Systems : Concepts, Methodologies, Tools, and Applications - Concepts, Methodologies, Tools, and Applications
volume
2
pages
27 pages
publisher
IGI Global
external identifiers
  • scopus:85059726634
ISBN
9781522570349
9781522570332
1522570330
DOI
10.4018/978-1-5225-7033-2.ch029
language
English
LU publication?
no
id
ac6662e2-bfc4-4fc3-b4b3-eda073a4360a
date added to LUP
2019-04-02 09:42:46
date last changed
2021-03-03 04:32:40
@inbook{ac6662e2-bfc4-4fc3-b4b3-eda073a4360a,
  abstract     = {<p>Computer science plays a major role in image segmentation and image processing applications. Despite the computational cost, PSO evaluated QCA approaches perform comparable to or better than their crisp counterparts. This novel approach, proposed in this chapter, has been found to enhance the functionality of the CA rule base and thus enhance the established potentiality of the fuzzy-based segmentation domain with the help of quantum cellular automata. This new unsupervised method is able to detect clusters using 2-dimensional quantum cellular automata model based on PSO evaluation. As a discrete, dynamical system, cellular automaton explores uniformly interconnected cells with states. In the second phase, it utilizes a 2-dimensional cellular automata to prioritize allocations of mixed pixels among overlapping land cover areas. The authors experiment on Tilaya Reservoir Catchment on Barakar River. The clustered regions are compared with well-known PSO, FCM, and k-means methods and also with the ground truth knowledge. The results show the superiority of the new method.</p>},
  author       = {Mahata, Kalyan and Das, Rajib and Das, Subhasish and Sarkar, Anasua},
  booktitle    = {Environmental Information Systems : Concepts, Methodologies, Tools, and Applications},
  isbn         = {9781522570349},
  language     = {eng},
  month        = {01},
  pages        = {679--705},
  publisher    = {IGI Global},
  title        = {Landcover change detection using PSO-evaluated quantum CA approach on multi-temporal remote-sensing watershed images},
  url          = {http://dx.doi.org/10.4018/978-1-5225-7033-2.ch029},
  doi          = {10.4018/978-1-5225-7033-2.ch029},
  volume       = {2},
  year         = {2018},
}