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- W2354891884 abstract "Markov Random Field ( MRF) model is a classical image texture analysis method, which has been widely used in image texture simulation and segmentation. However, when the classical simulated annealing algorithm is used to compute a global optimal solution, it cannot satisfy the performance requirements of texture analysis and processing due to less efficiency. A fitness function which could determine texture class was designed, and the use of Particle Swarm Optimization ( PSO) was proposed to calculate the optimal solution of it. Based on the proposed method, texture segmentation of remote sensing images was carried out. Compared with the simulated annealing algorithm, the experimental results show that PSO algorithm can reduce the computational complexity and it is a more effectively optimal method of image segmentation." @default.
- W2354891884 created "2016-06-24" @default.
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- W2354891884 date "2010-01-01" @default.
- W2354891884 modified "2023-09-27" @default.
- W2354891884 title "Combination of MRF model and particle swarm optimization algorithm for texture segmentation of remote sensing images" @default.
- W2354891884 hasPublicationYear "2010" @default.
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