DocumentCode
1741624
Title
Vector probability diffusion
Author
Pardo, Alvaro ; Sapiro, Guillermo
Author_Institution
Inst. of Math., Univ. de la Republica, Montevideo, Uruguay
Volume
1
fYear
2000
fDate
2000
Firstpage
884
Abstract
A method for isotropic and anisotropic diffusion of vector probabilities in general, and posterior probabilities in particular, is introduced. The technique is based on diffusing via coupled partial differential equations restricted to the semi-hyperplane corresponding to probability functions. Both the partial differential equations and their corresponding numerical implementation guarantee that the vector remains a probability vector, having all its components positive and adding to one. Applying the method to posterior probabilities in classification problems, spatial and contextual coherence is introduced before the MAP decision, thereby improving the classification results
Keywords
image classification; image segmentation; partial differential equations; probability; vectors; MAP decision; anisotropic diffusion; classification problems; contextual coherence; coupled partial differential equations; image classification; image segmentation; isotropic diffusion; numerical implementation; posterior probabilities; probability functions; semi-hyperplane; spatial coherence; vector probability diffusion; Anisotropic magnetoresistance; Diffusion processes; Engineering profession; Image segmentation; Labeling; Layout; Markov random fields; Mathematics; Partial differential equations; Spatial coherence;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location
Vancouver, BC
ISSN
1522-4880
Print_ISBN
0-7803-6297-7
Type
conf
DOI
10.1109/ICIP.2000.901101
Filename
901101
Link To Document