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Kernel-Based Image Filtering: Fast Algorithms and Applications

Ghosh, S and Chaudhury, KN (2019) Kernel-Based Image Filtering: Fast Algorithms and Applications. In: 26th IEEE International Conference on Image Processing, ICIP 2019, 22 - 25 September 2019, Taipei, pp. 3018-3019.

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Official URL: https://doi.org/10.1109/ICIP.2019.8803364


Image filtering is a fundamental preprocessing task in computer vision and image processing. While the dominant applications of kernel filtering are enhancement and denoising, it can also be used as a powerful regularizer for image reconstruction. In general, the brute-force implementations of kernel filtering is prohibitively expensive. They are often too slow for real-time applications. In the first half of the thesis, we propose fast algorithms for bilateral filtering (BLF) and nonlocal means (NLM). In particular, we demonstrate that by using the Fourier approximation of the underlying kernel, we can obtain state-of-the-art fast algorithms for BLF of grayscale images. We next extend the idea for fast filtering of color images, which involves the approximation of a three-dimensional kernel. We next propose a fast separable formulation for NLM of grayscale images. In the second half of the dissertation, we turn to some applications of kernel filtering. We introduce a scale-adaptive variant of BLF that is used for suppressing fine textures in images. We develop a fast implementation of a symmetrized variant of NLM that is used for regularization (i.e., as a prior) within the plug-and-play framework for image restoration. The core idea can be extended to other forms of kernel filtering. © 2019 IEEE.

Item Type: Conference Paper
Publication: Proceedings - International Conference on Image Processing, ICIP
Publisher: IEEE Computer Society
Additional Information: The copyright for this article belongs to Association for Computing Machinery, Inc
Keywords: bilateral filter; fast algorithm; Fourier approximation; low-light enhancement; retinex
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 06 Jan 2023 06:42
Last Modified: 06 Jan 2023 06:42
URI: https://eprints.iisc.ac.in/id/eprint/78813

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