Segmentation of noisy images using information theory based approaches
- Resource Type
- Conference
- Authors
- Galland, Frederic; Refregier, Philippe
- Source
- 2008 First Workshops on Image Processing Theory, Tools and Applications Image Processing Theory, Tools and Applications, 2008. IPTA 2008. First Workshops on. :1-4 Nov, 2008
- Subject
- Signal Processing and Analysis
Computing and Processing
General Topics for Engineers
Image segmentation
Information theory
Image processing
Stochastic processes
Image analysis
Physics
Markov random fields
Stochastic resonance
Active contours
Statistics
Segmentation
Stochastic complexity
Minimum Description Length
Noise in imaging systems
- Language
- ISSN
- 2154-5111
2154-512X
In this presentation, we propose to discuss some interesting properties of segmentation techniques based on the minimization of the stochastic complexity. We emphasize the general framework provided by the minimization of the stochastic complexity for segmentation purpose, some of its main advantages and also some of the motivating perspectives that are open by such approaches. We illustrate this presentation with different results obtained in our research group with polygonal parametric shape descriptions, level set models of contours and polygonal grids to partition images into an arbitrary number of homogeneous regions.