Ghosh, S and Gavaskar, RG and Panda, D and Chaudhury, KN (2020) Fast Scale-Adaptive Bilateral Texture Smoothing. In: IEEE Transactions on Circuits and Systems for Video Technology, 30 (7). pp. 2015-2026.
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Abstract
In the classical bilateral filter, a range kernel is used together with a spatial kernel for smoothing out fine details while simultaneously preserving edges. More recently, it has been demonstrated that even coarse textures can be smoothed using joint bilateral filtering. In this paper, we demonstrate that the superior texture filtering results can be obtained by adapting the spatial kernel at each pixel. To the best of our knowledge, spatial adaptation (of the bilateral filter) has not been explored for texture smoothing. The rationale behind adapting the spatial kernel is that one cannot smooth beyond a certain level using a fixed spatial kernel, no matter how we manipulate the range kernel. In fact, we should simply aggregate more pixels using a sufficiently wide spatial kernel to locally enhance the smoothing. Based on this reasoning, we propose to use the classical bilateral filter for texture smoothing, where we adapt the width of the spatial kernel at each pixel. We describe a simple and efficient gradient-based rule for the latter task. The attractive aspect is that we are able to develop a fast algorithm that can accelerate the computations by an order without visibly compromising the filtering quality. We demonstrate that our method outperforms classical bilateral filtering, joint bilateral filtering, and other filtering methods, and is competitive with the optimization methods. We also present some applications of texture smoothing using the proposed method. © 1991-2012 IEEE.
Item Type: | Journal Article |
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Publication: | IEEE Transactions on Circuits and Systems for Video Technology |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Additional Information: | Copy right for this article belongs to Institute of Electrical and Electronics Engineers Inc. |
Keywords: | Aggregates; Nonlinear filtering; Pixels, Bilateral filtering; Bilateral filters; Fast algorithms; Filtering method; Filtering qualities; Optimization method; Spatial adaptation; Spatial kernels, Textures |
Department/Centre: | Division of Electrical Sciences > Electrical Engineering |
Date Deposited: | 20 Nov 2020 07:24 |
Last Modified: | 20 Nov 2020 07:24 |
URI: | http://eprints.iisc.ac.in/id/eprint/66093 |
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