DocumentCode
2344539
Title
Adaptive edge detection in compound Gauss-Markov random fields using the minimum description length principle
Author
Figueiredo, Mário A T ; Leitão, Joel H N
Author_Institution
Dept. de Engenharia Electrotecnica e de Comput., Inst. Superior Tecnico, Lisbon, Portugal
fYear
1994
fDate
27-29 Oct 1994
Firstpage
62
Abstract
Edge location in compound Gauss-Markov random fields (CGMRF) is formulated as a parameter estimation problem. Since the number of parameters is unknown, a minimum-description-length (MDL) criterion is proposed for image restoration based on the CGMRF model
Keywords
Gaussian processes; Markov processes; adaptive signal detection; edge detection; image restoration; parameter estimation; random processes; MDL criterion; adaptive edge detection; compound Gauss-Markov random fields; image restoration; minimum description length principle; parameter estimation; AWGN; Bayesian methods; Gaussian processes; Image edge detection; Image restoration; Maximum likelihood estimation; Parameter estimation; Signal restoration; Telecommunication computing; Writing;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory and Statistics, 1994. Proceedings., 1994 IEEE-IMS Workshop on
Conference_Location
Alexandria, VA
Print_ISBN
0-7803-2761-6
Type
conf
DOI
10.1109/WITS.1994.513891
Filename
513891
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