Integration of Gibbs Markov random field and hopfield-type neural networks for unsupervised change detection in remotely sensed multitemporal images

IEEE Transactions on Image Processing

Volumn 22, Issue 8, 2013, Pages 3087-3096

  Ghosh, Ashish ^a   Subudhi, Badri Narayan ^a   Bruzzone, Lorenzo ^b  

^a INDIAN STATISTICAL INSTITUTE   (India)

^b UNIVERSITY OF TRENTO   (Italy)

Author keywords

Change detection; hopfield neural network; markov random field (MRF); maximum a posteriori probability (MAP) estimation; multitemporal images; remote sensing

Indexed keywords

CHANGE DETECTION; EXPECTATION-MAXIMIZATION ALGORITHMS; HOPFIELD TYPE NEURAL NETWORKS; MARKOV RANDOM FIELDS; MAXIMUM A POSTERIORI PROBABILITY ESTIMATIONS (MAP); MULTI-TEMPORAL IMAGE; MULTI-TEMPORAL REMOTE SENSING; MULTISPECTRAL REMOTE SENSING IMAGE;

ALGORITHMS; ESTIMATION; GAUSSIAN DISTRIBUTION; GRAPHIC METHODS; HOPFIELD NEURAL NETWORKS; IMAGE RECONSTRUCTION; IMAGE SEGMENTATION; MARKOV PROCESSES; PIXELS; REMOTE SENSING;

SIGNAL DETECTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; PROBABILITY; REMOTE SENSING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; SYSTEM ANALYSIS; PROCEDURES;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DATA INTERPRETATION, STATISTICAL; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MARKOV CHAINS; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; REMOTE SENSING TECHNOLOGY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE; SYSTEMS INTEGRATION;

EID: 84878499480     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2013.2259833     Document Type: Article

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