SVM for edge-preserving filtering

Qingxiong Yang, Shengnan Wang, Narendra Ahuja

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a new method to construct an edge-preserving filter which has very similar response to the bilateral filter. The bilateral filter is a normalized convolution in which the weighting for each pixel is determined by the spatial distance from the center pixel and its relative difference in intensity range. The spatial and range weighting functions are typically Gaussian in the literature. In this paper, we cast the filtering problem as a vector-mapping approximation and solve it using a support vector machine (SVM). Each pixel will be represented as a feature vector comprising of the exponentiation of the pixel intensity, the corresponding spatial filtered response, and their products. The mapping function is learned via ε-SVM regression using the feature vectors and the corresponding bilateral filtered values from the training image. The major computation involved is the computation of the spatial filtered responses of the exponentiation of the original image which is invariant to the filter size given that an IIR O(1) solution is available for the spatial filtering kernel. To our knowledge, this is the first learning-based O(1) bilateral filtering method. Unlike previous O(1) methods, our method is valid for both low and high range variance Gaussian and the computational complexity is independent of the range variance value. Our method is also the fastest O(1) bilateral filtering yet developed. Besides, our method allows varying range variance values, based on which we propose a new bilateral filtering method avoiding the over-smoothing or under-smoothing artifacts in traditional bilateral filter.

Original languageEnglish (US)
Title of host publication2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
Pages1775-1782
Number of pages8
DOIs
StatePublished - Aug 31 2010
Event2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 - San Francisco, CA, United States
Duration: Jun 13 2010Jun 18 2010

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Other

Other2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
CountryUnited States
CitySan Francisco, CA
Period6/13/106/18/10

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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    Yang, Q., Wang, S., & Ahuja, N. (2010). SVM for edge-preserving filtering. In 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 (pp. 1775-1782). [5539847] (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). https://doi.org/10.1109/CVPR.2010.5539847