ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

On Fast Bilateral Filtering Using Fourier Kernels

Ghosh, Sanjay and Chaudhury, Kunal N (2016) On Fast Bilateral Filtering Using Fourier Kernels. In: IEEE SIGNAL PROCESSING LETTERS, 23 (5). pp. 570-574.

Full text not available from this repository. (Request a copy)
Official URL: http://dx.doi.org/10.1109/LSP.2016.2539982


It was demonstrated in earlier work that, by approximating its range kernel using shiftable functions, the nonlinear bilateral filter can be computed using a series of fast convolutions. Previous approaches based on shiftable approximation have, however, been restricted to Gaussian range kernels. In this work, we propose a novel approximation that can be applied to any range kernel, provided it has a pointwise-convergent Fourier series. More specifically, we propose to approximate the Gaussian range kernel of the bilateral filter using a Fourier basis, where the coefficients of the basis are obtained by solving a series of least-squares problems. The coefficients can be efficiently computed using a recursive form of the QR decomposition. By controlling the cardinality of the Fourier basis, we can obtain a good tradeoff between the run-time and the filtering accuracy. In particular, we are able to guarantee subpixel accuracy for the overall filtering, which is not provided by the most existing methods for fast bilateral filtering. We present simulation results to demonstrate the speed and accuracy of the proposed algorithm.

Item Type: Journal Article
Additional Information: Copy right for this article belongs to the IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Keywords: Accuracy; bilateral filter; fast algorithm; Fourier basis; shiftability
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 28 Apr 2016 05:13
Last Modified: 28 Apr 2016 05:13
URI: http://eprints.iisc.ac.in/id/eprint/53707

Actions (login required)

View Item View Item