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A Quaternion Framework for Color Image Smoothing and Segmentation
- Source :
- International Journal of Computer Vision. 91:233-250
- Publication Year :
- 2010
- Publisher :
- Springer Science and Business Media LLC, 2010.
-
Abstract
- In this paper, we present feature/detail preserving models for color image smoothing and segmentation using the Hamiltonian quaternion framework. First, we introduce a novel quaternionic Gabor filter (QGF) which can combine the color channels and the orientations in the image plane. We show that these filters are optimally localized both in the spatial and frequency domains and provide a good approximation to quaternionic quadrature filters. Using the QGFs, we extract the local orientation information in the color images. Second, in order to model this derived orientation information, we propose continuous mixtures of appropriate exponential basis functions and derive analytic expressions for these models. These analytic expressions take the form of spatially varying kernels which, when convolved with a color image or the signed distance function of an evolving contour (placed in the color image), yield a detail preserving smoothing and segmentation, respectively. Several examples on widely used image databases are shown to depict the performance of our algorithms.
- Subjects :
- Color histogram
Demosaicing
Color image
business.industry
Binary image
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Scale-space segmentation
Pattern recognition
Image segmentation
Image texture
Artificial Intelligence
Computer Science::Computer Vision and Pattern Recognition
Computer Vision and Pattern Recognition
Artificial intelligence
business
Software
Image gradient
ComputingMethodologies_COMPUTERGRAPHICS
Mathematics
Subjects
Details
- ISSN :
- 15731405 and 09205691
- Volume :
- 91
- Database :
- OpenAIRE
- Journal :
- International Journal of Computer Vision
- Accession number :
- edsair.doi...........5904b49e8ad93d6316600f8bcdb1314b