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Edge-Aware Filtering with Local Polynomial Approximation and Rectangle-Based Weighting | IEEE Journals & Magazine | IEEE Xplore

Edge-Aware Filtering with Local Polynomial Approximation and Rectangle-Based Weighting


Abstract:

This paper presents a novel method for performing guided image filtering using local polynomial approximation (LPA) with range guidance. In our method, the LPA is introdu...Show More

Abstract:

This paper presents a novel method for performing guided image filtering using local polynomial approximation (LPA) with range guidance. In our method, the LPA is introduced into a multipoint framework for reliable model regression and better preservation on image spatial variation which usually contains the essential information in the input image. In addition, we develop a weighting scheme which has the spatial flexibility during the filtering process. All components in our method are efficiently implemented and a constant computation complexity is achieved. Compared with conventional filtering methods, our method provides clearer boundaries and performs especially better in recovering spatial variation from noisy images. We conduct a number of experiments for different applications: depth image upsampling, joint image denoising, details enhancement, and image abstraction. Both quantitative and qualitative comparisons demonstrate that our method outperforms state-of-the-art methods.
Published in: IEEE Transactions on Cybernetics ( Volume: 46, Issue: 12, December 2016)
Page(s): 2693 - 2705
Date of Publication: 26 October 2015

ISSN Information:

PubMed ID: 26513818

References

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