Segmentation of very high resolution remote sensing imagery of urban areas using particle swarm optimization algorithm

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6111 LNCS, Issue PART 1, 2010, Pages 81-88

  Bedawi, Safaa M ^a   Kamel, Mohamed S ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Aerial Images; and Clustering Based Segmentation; Particle Swarm Optimization (PSO); Remote Sensing; Swarm Intelligence

Indexed keywords

AERIAL IMAGES; AND CLUSTERING-BASED SEGMENTATION; CLUSTERING RESULTS; CONVENTIONAL CLUSTERING; DENSE URBAN ENVIRONMENTS; HIER-ARCHICAL CLUSTERING; HIGH RESOLUTION; HIGH RESOLUTION REMOTE SENSING IMAGES; K-MEANS; K-MEANS ALGORITHM; K-MEANS CLUSTERING ALGORITHM; NOISY IMAGE; PARTICLE SWARM OPTIMIZATION ALGORITHM; PSO ALGORITHMS; SENSED IMAGE; SOLUTION SPACE; SWARM INTELLIGENCE; URBAN AREAS; VERY HIGH RESOLUTION; VOLUME DATA;

CELLULAR AUTOMATA; CLUSTER ANALYSIS; IMAGE ANALYSIS; IMAGE RECONSTRUCTION; IMAGE SEGMENTATION; PARTICLE SWARM OPTIMIZATION (PSO); REMOTE SENSING; SPACE OPTICS;

CLUSTERING ALGORITHMS;

EID: 77955442890     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-13772-3_9     Document Type: Conference Paper

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