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Fast Adaptive Bilateral Filtering

Gavaskar, Ruturaj G and Chaudhury, Kunal N (2019) Fast Adaptive Bilateral Filtering. In: IEEE TRANSACTIONS ON IMAGE PROCESSING, 28 (2). pp. 779-790.

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Official URL: http://dx.doi.org/10.1109/TIP.2018.2871597

Abstract

In the classical bilateral filter, a fixed Gaussian range kernel is used along with a spatial kernel for edge-preserving smoothing. We consider a generalization of this filter, the so-called adaptive bilateral filter, where the center and width of the Gaussian range kernel are allowed to change from pixel to pixel. Though this variant was originally proposed for sharpening and noise removal, it can also be used for other applications, such as artifact removal and texture filtering. Similar to the bilateral filter, the brute-force implementation of its adaptive counterpart requires intense computations. While several fast algorithms have been proposed in the literature for bilateral filtering, most of them work only with a fixed range kernel. In this paper, we propose a fast algorithm for adaptive bilateral filtering, whose complexity does not scale with the spatial filter width. This is based on the observation that the concerned filtering can be performed purely in range space using an appropriately defined local histogram. We show that by replacing the histogram with a polynomial and the finite range-space sum with an integral, we can approximate the filter using analytic functions. In particular, an efficient algorithm is derived using the following innovations: the polynomial is fitted by matching its moments to those of the target histogram (this is done using fast convolutions), and the analytic functions are recursively computed using integration-by-parts. Our algorithm can accelerate the brute-force implementation by at least 20x, without perceptible distortions in the visual quality. We demonstrate the effectiveness of our algorithm for sharpening, JPEG deblocking, and texture filtering.

Item Type: Journal Article
Publication: IEEE TRANSACTIONS ON IMAGE PROCESSING
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Additional Information: Copy right for this article belong to IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords: Bilateral filtering; adaptive; approximation; fast algorithm; histogram
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 22 Oct 2018 15:04
Last Modified: 22 Oct 2018 15:04
URI: http://eprints.iisc.ac.in/id/eprint/60914

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