2007
DOI: 10.1109/tgrs.2007.892604
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Multiobjective Genetic Clustering for Pixel Classification in Remote Sensing Imagery

Abstract: An important approach for unsupervised landcover classification in remote sensing images is the clustering of pixels in the spectral domain into several fuzzy partitions. In this paper, a multiobjective optimization algorithm is utilized to tackle the problem of fuzzy partitioning where a number of fuzzy cluster validity indexes are simultaneously optimized. The resultant set of near-Pareto-optimal solutions contains a number of nondominated solutions, which the user can judge relatively and pick up the most p… Show more

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Cited by 274 publications
(159 citation statements)
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References 7 publications
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“…While selection is random any individual has the choice to become a parent, selection is clearly biased towards fitted individuals. 64 Parents are not required to be distinctive for any iteration; fit individuals may produce many offspring's the crossover is selected at random and mutation is applied to all individuals in the new population. With probability P m , each bit on every string is inverted.…”
Section: Genetic Algorithms (Gas)mentioning
confidence: 99%
See 1 more Smart Citation
“…While selection is random any individual has the choice to become a parent, selection is clearly biased towards fitted individuals. 64 Parents are not required to be distinctive for any iteration; fit individuals may produce many offspring's the crossover is selected at random and mutation is applied to all individuals in the new population. With probability P m , each bit on every string is inverted.…”
Section: Genetic Algorithms (Gas)mentioning
confidence: 99%
“…69 2013 MOPs are used to embark upon the arduousness of fuzzy partitioning where a number of fuzzy cluster validity indices are simultaneously optimized. The resultant set of near-Pareto-optimal answers contains a number of non-dominated answers, which the user can referee relatively and choose upon the most undertaking one according to the problem necessity; Real-coded encoding of the cluster centers is utilized for this principle [64].…”
Section: ------------------------------------------------------------mentioning
confidence: 99%
“…Apart from the classification methods presented in [14,12,3], several others have been proposed recently [8,13,1,10,2]. The novelty of these approaches relies on: resolution and number of bands of ISRs; type of extracted features; used learning technique, and level of discrimination among the classes of the image (some studies include all the vegetation types in the same class, for example).…”
Section: Related Workmentioning
confidence: 99%
“…al [13] and Bandyopadhyay et. al [1] use Genetic algorithms (GA). The former uses GA to find the configuration parameters of a neural network while the latter uses GA for clustering the pixels of the RSIs.…”
Section: Related Workmentioning
confidence: 99%
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