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LLSURE: Local Linear SURE-Based Edge-Preserving Image Filtering

Published: 01 January 2013 Publication History

Abstract

In this paper, we propose a novel approach for performing high-quality edge-preserving image filtering. Based on a local linear model and using the principle of Stein's unbiased risk estimate as an estimator for the mean squared error from the noisy image only, we derive a simple explicit image filter which can filter out noise while preserving edges and fine-scale details. Moreover, this filter has a fast and exact linear-time algorithm whose computational complexity is independent of the filtering kernel size; thus, it can be applied to real time image processing tasks. The experimental results demonstrate the effectiveness of the new filter for various computer vision applications, including noise reduction, detail smoothing and enhancement, high dynamic range compression, and flash/no-flash denoising.

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  • (2021)Non-local/local image filters using fast eigenvalue filtering2015 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2015.7351690(4659-4663)Online publication date: 9-Mar-2021
  • (2019)An Adaptive SVD based De-Noising Filtering Scheme for parallel MRIProceedings of the 2019 3rd International Conference on Compute and Data Analysis10.1145/3314545.3314560(152-156)Online publication date: 14-Mar-2019
  • (2019)X-Ray Enhancement Based on Component Attenuation, Contrast Adjustment, and Image FusionIEEE Transactions on Image Processing10.1109/TIP.2018.286563728:1(127-141)Online publication date: 1-Jan-2019
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  1. LLSURE: Local Linear SURE-Based Edge-Preserving Image Filtering

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      cover image IEEE Transactions on Image Processing
      IEEE Transactions on Image Processing  Volume 22, Issue 1
      January 2013
      413 pages

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      IEEE Press

      Publication History

      Published: 01 January 2013

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      • (2021)Non-local/local image filters using fast eigenvalue filtering2015 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2015.7351690(4659-4663)Online publication date: 9-Mar-2021
      • (2019)An Adaptive SVD based De-Noising Filtering Scheme for parallel MRIProceedings of the 2019 3rd International Conference on Compute and Data Analysis10.1145/3314545.3314560(152-156)Online publication date: 14-Mar-2019
      • (2019)X-Ray Enhancement Based on Component Attenuation, Contrast Adjustment, and Image FusionIEEE Transactions on Image Processing10.1109/TIP.2018.286563728:1(127-141)Online publication date: 1-Jan-2019
      • (2018)Interpreting and Extending the Guided Filter via Cyclic Coordinate DescentIEEE Transactions on Image Processing10.1109/TIP.2018.286972028:2(767-778)Online publication date: 10-Oct-2018
      • (2018)Relative reductive structure-aware regression filterJournal of Computational and Applied Mathematics10.1016/j.cam.2017.05.047329:C(244-255)Online publication date: 1-Feb-2018
      • (2017)An adaptive edge-preserving image denoising technique using patch-based weighted-SVD filtering in wavelet domainMultimedia Tools and Applications10.1007/s11042-015-3154-876:2(1659-1679)Online publication date: 1-Jan-2017
      • (2016)A survey of edge-preserving image denoising methodsInformation Systems Frontiers10.1007/s10796-014-9527-018:1(159-170)Online publication date: 1-Feb-2016
      • (2015)LAPBInformation Sciences: an International Journal10.1016/j.ins.2014.09.060294:C(164-181)Online publication date: 10-Feb-2015
      • (2015)The role of real-time in biomedical scienceComputers in Biology and Medicine10.1016/j.compbiomed.2014.12.02458:C(73-84)Online publication date: 1-Mar-2015
      • (2015)An adaptive edge-preserving image denoising technique using tetrolet transformsThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-014-0993-731:5(657-674)Online publication date: 1-May-2015
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