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A generalization of median filtering using linear combinations of order statistics
Abstract
We consider a class of nonlinear filters whose output is given by a linear combination of the order statistics of the input sequence. Assuming a constant signal in white noise, the coefficients in the linear combination are chosen to minimize the output MSE for several noise distributions. It is shown that the optimal order statistic filter (OSF) tends toward the median filter as the noise becomes more impulsive. The optimal OSF is applied to an actual noisy image and is shown to perform well, combining properties of both the averaging and median filters. A more general design scheme for applications involving nonconstant signals is also given.
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“While these features do not yield high video quality prediction performance when used in isolation”
From Blind Prediction of Natural Video Quality (2014) · cites this paper as [47]
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“they do capture spatial aspects of distortion that are not contained in the other features and thereby boost prediction performance.”
From Blind Prediction of Natural Video Quality (2014) · cites this paper as [47]
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References 14 · Cited by 580
Research works printed but not linked: 15
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Metadata
- Authors
- Bovik, A., Huang, T., & Munson, D.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- Venue
- IEEE Transactions on Acoustics, Speech, and Signal Processing
- Published
- 1983-12
- Volume
- 31
- Issue
- 6
- Pages
- 1342-1350
- ISSN
- 0096-3518 (ISSN-L)
- OpenAlex
- W2007148047
- Cited by
- 580
- References
- 14
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 4 · 2023: 5 · 2022: 7 · 2021: 6 · 2020: 5 · 2019: 9 · 2018: 5 · 2017: 4 · 2016: 8 · 2015: 17 · 2014: 8 · 2013: 7 · 2012: 16
- FWCI
- 7.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Acoustics Speech and Signal Processing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
- Physical Sciences › Computer Science › Signal Processing › Advanced Adaptive Filtering Techniques
- Physical Sciences › Computer Science › Signal Processing › Digital Filter Design and Implementation
- Keywords
- median filter, order statistic filters, filter optimization, minimum mean square error, impulsive noise, image denoising, averaging filter
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