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Compressive Adaptive Bilateral Filtering

Nair, P and Gavaskar, RG and Chaudhury, KN (2020) Compressive Adaptive Bilateral Filtering. In: 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, 4-8, May 2020, Barcelona, Spain, pp. 2078-2082.

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Official URL: https://dx.doi.org/10.1109/ICASSP40776.2020.905327...


We propose a fast algorithm for an adaptive variant of the classical bilateral filter, where the range kernel is allowed to vary from pixel to pixel. Several fast and accurate algorithms have been proposed for bilateral filtering, but they assume that the same range kernel is used at each pixel and hence cannot be used for adaptive bilateral filtering (ABF). Only recently, it was shown that fast algorithms for ABF can be developed by approximating the local histogram around each pixel using polynomials. The present algorithm is derived using an entirely different approximation, namely, the range kernels across all pixels are jointly approximated (compressed) using singular value decomposition (SVD). The SVD involves a very large matrix and cannot be computed exactly; however, we are able to get a sufficiently accurate approximation using the Nyström method (without populating/storing the entire matrix). We show that this SVD-type decomposition allows us to approximate the adaptive bilateral filter using fast convolutions. To demonstrate the speed and accuracy of the proposed algorithm in relation to existing algorithms, we use it for texture filtering, JPEG deblocking, and detail enhancement. © 2020 IEEE.

Item Type: Conference Paper
Publication: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: The copyright of this article belongs to Institute of Electrical and Electronics Engineers Inc.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 28 Aug 2020 07:06
Last Modified: 28 Aug 2020 07:06
URI: http://eprints.iisc.ac.in/id/eprint/66374

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