Gauss-Markov measure field models for low-level vision

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 23, Issue 4, 2001, Pages 337-348

  Marroquin, Jose L ^a   Velasco, Fernando A ^b   Rivera, Mariano ^a   Nakamura, Miguel ^a  

^a CENTRO DE INVESTIGACIÓN EN MATEMÁTICAS   (Mexico)

^b UNIVERSIDAD MICHOACANA DE SAN NICOLÁS DE HIDALGO   (Mexico)

Author keywords

Bayes methods; Estimation theory; Gaussian distributions; Image classification; Image segmentation; Markov processes; Probability; Simulated annealing

Indexed keywords

BAYES METHOD; ESTIMATION THEORY; GAUSS DISTRIBUTIONS; IMAGE CLASSIFICATION; IMAGE FILTERING; IMAGE QUANTIZATION; MARKOV RANDOM FIELDS;

ALGORITHMS; APPROXIMATION THEORY; COMPUTER SIMULATION; FINITE DIFFERENCE METHOD; IMAGE RECONSTRUCTION; IMAGE SEGMENTATION; MARKOV PROCESSES; MAXIMUM LIKELIHOOD ESTIMATION; PARTIAL DIFFERENTIAL EQUATIONS; PROBABILITY DISTRIBUTIONS; SIMULATED ANNEALING; STATE SPACE METHODS;

COMPUTER VISION;

EID: 0035306348     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/34.917570     Document Type: Article

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