Realizations and parameter estimation for line processes

Author

Derin, Haluk ; Guler, Sadiye

Author_Institution

Dept. of Electr. & Comput. Eng., Massachusetts Univ., Amherst, MA, USA

fYear

1990

fDate

3-6 Apr 1990

Firstpage

2213

Abstract

The Markov line process that has been used in some image segmentation and restoration studies is investigated. Realizations from this model are presented for a wide range of parameter values, and the effects of certain parameters are studied. The maximum pseudolikelihood (MPL) estimation procedure is implemented for the Markov line process. The MPL procedure is applied to several images generated from the model as well as to a hand-drawn image and the edge-detector output of a natural image. It is expected that improved segmentation and restoration results can be obtained, if the Markov line process model is fine-tuned to the class of images under consideration, by estimating the parameters of some typical images in that class

Keywords

Markov processes; parameter estimation; picture processing; signal synthesis; Markov line process; edge-detector output; hand-drawn image; image segmentation; maximum pseudolikelihood estimation; natural image; parameter estimation; Detectors; Geometry; Image edge detection; Image generation; Image restoration; Image segmentation; Lattices; Markov random fields; Parameter estimation; Pixel;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Conference_Location

Albuquerque, NM

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1990.116002

Filename

116002