DocumentCode
2069322
Title
Spatial entropy: a tool for controlling contextual classification convergence
Author
MaÎtre, Henri ; Bloch, Isabelle ; Sigelle, Marc
Author_Institution
Dept. Images, Telecom Paris, France
Volume
2
fYear
1994
fDate
13-16 Nov 1994
Firstpage
212
Abstract
A new kind of entropy is proposed, which associates spatial and radiometric properties of images. The possible use of this entropy is shown firstly to measure the effect of picture processing algorithms, then to control the evolution of iterative contextual classification algorithms like Markov random fields
Keywords
Markov processes; convergence of numerical methods; entropy; image classification; iterative methods; Markov random fields; contextual classification convergence; iterative contextual classification algorithms; picture processing algorithms; radiometric properties; spatial entropy; spatial properties; Convergence; Entropy; Gain measurement; Image processing; Iterative algorithms; Markov random fields; Pattern recognition; Pixel; Radiometry; Signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
Conference_Location
Austin, TX
Print_ISBN
0-8186-6952-7
Type
conf
DOI
10.1109/ICIP.1994.413562
Filename
413562
Link To Document