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Kernel Regression for Image Processing and Reconstruction.
- Source :
-
IEEE Transactions on Image Processing . Feb2007, Vol. 16 Issue 2, p349-366. 18p. 8 Black and White Photographs, 4 Graphs. - Publication Year :
- 2007
-
Abstract
- In this paper, we make contact with the field of non-parametric statistics and present a development and generalization of tools and results for use in image processing and reconstruction. In particular, we adapt and expand kernel regression ideas for use in image denoising, upscaling, interpolation, fusion, and more. Furthermore, we establish key relationships with some popular existing methods and show how several of these algorithms, including the recently popularized bilateral filter, are special cases of the proposed framework. The resulting algorithms and analyses are amply illustrated with practical examples. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10577149
- Volume :
- 16
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Image Processing
- Publication Type :
- Academic Journal
- Accession number :
- 23962970
- Full Text :
- https://doi.org/10.1109/TIP.2006.888330