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Median filter

About: Median filter is a research topic. Over the lifetime, 12479 publications have been published within this topic receiving 178253 citations.


Papers
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Proceedings ArticleDOI
03 Jul 2013
TL;DR: A comparative study of seven filters, namely Lee, Frost, Median, Speckle Reduction Anisotropic Diffusion (SRAD), Perona-Malik's An isotropic diffusion (PMAD) filter, Spekle Reduction Bilateral Filter (SRBF) and Speckel Reduction filter based on soft thresholding in the Wavelet transform, to determine which despeckling algorithm is most effective and optimal for real-time implementation.
Abstract: At present, ultrasound is one of the essential tools for noninvasive medical diagnosis. However, speckle noise is inherent in medical ultrasound images and it is the cause for decreased resolution and contrast-to-noise ratio. Low image quality is an obstacle for effective feature extraction, recognition, analysis, and edge detection; it also affects image interpretation by doctor and the accuracy of computer-assisted diagnostic techniques. Thus, speckle reduction is significant and critical step in pre-processing of ultrasound images. Many speckle reduction techniques have been studied by researchers, but to date there is no comprehensive method that takes all the constraints into consideration. In this paper we discuss seven filters, namely Lee, Frost, Median, Speckle Reduction Anisotropic Diffusion (SRAD), Perona-Malik's Anisotropic Diffusion (PMAD) filter, Speckle Reduction Bilateral Filter (SRBF) and Speckle Reduction filter based on soft thresholding in the Wavelet transform. A comparative study of these filters has been made in terms of preserving the features and edges as well as effectiveness of de-noising.We computed five established evaluation metrics in order to determine which despeckling algorithm is most effective and optimal for real-time implementation. In addition, the experimental results have been demonstrated by filtered images and statistical data table.

58 citations

Journal ArticleDOI
TL;DR: A fast two-dimensional median filtering algorithm that is designed in such a way that in order to find the median of a window, the results obtained during the partitioning of the previous window are used.
Abstract: The median of a set of numbers is a number which partitions the given set, excluding that number, into two subsets with an equal number of elements such that the number is greater than or equal to the elements in one subset and less than or equal to in the other In image processing, in order to compute the running median, the window is moved from one neighborhood to the next In this paper, a fast two-dimensional median filtering algorithm is proposed The algorithm is designed in such a way that in order to find the median of a window, the results obtained during the partitioning of the previous window are used Test results obtained by running the algorithm on VAX 11/780 are presented and its performance is compared with the Huang's histogram algorithm for median filtering It is shown that the proposed algorithm's execution time is faster and is independent of the number of bits used to represent the data values The novel features in the algorithm design that contribute to fast execution are also presented

58 citations

Proceedings ArticleDOI
02 Dec 1997
TL;DR: Three realizations of median filter are described, built into as few as one field programmable logic device, which is capable of processing an incoming video data stream at a maximum of around 30 MS/s.
Abstract: The median filter is an effective device for the removal of impulse-based noise on video signals. This is due to the partial averaging effect of the median filter and its biasing of the input stream, rather than straight mathematical averaging. In this paper, we describe three realizations of median filter, built into as few as one field programmable logic device, which is capable of processing an incoming video data stream at a maximum (programmable logic device partially dependent) of around 30 MS/s. In total, four designs are considered, with a primary design, two variations on the primary design and an asynchronous version based on the primary design. Simulation of the primary design (both synchronous and asynchronous) has demonstrated its potential for reducing the area requirements of a median filter whilst not sacrificing either speed or accuracy.

58 citations

Journal ArticleDOI
TL;DR: In this paper, a multiscale kernel principal component analysis (MSKPCA) based on sliding median filter (SFM) is proposed for fault detection in nonlinear system with outliers.
Abstract: In this paper the multiscale kernel principal component analysis (MSKPCA) based on sliding median filter (SFM) is proposed for fault detection in nonlinear system with outliers. The MSKPCA based on SFM (SFM-MSKPCA) algorithm is first proposed and applied to process monitoring. The advantages of SFM-MSKPCA are: (1) the dynamical multiscale monitoring method is proposed which combining the Kronecker production, the wavelet decomposition technique, the sliding median filter technique and KPCA. The Kronecker production is first used to build the dynamical model; (2) there are more disturbances and noises in dynamical processes compared to static processes. The sliding median filter technique is used to remove the disturbances and noises; (3) SFM-MSKPCA gives nonlinear dynamic interpretation compared to MSPCA; (4) by decomposing the original data into multiple scales, SFM-MSKPCA analyze the dynamical data at different scales, reconstruct scales contained important information by IDWT, eliminate the effects of the noises in the original data compared to kernel principal component analysis (KPCA). To demonstrate the feasibility of the SFM-MSKPCA method, its process monitoring abilities are tested by simulation examples, and compared with the monitoring abilities of the KPCA and MSPCA method on the quantitative basis. The fault detection results and the comparison show the superiority of SFM-MSKPCA in fault detection.

58 citations

Journal ArticleDOI
TL;DR: Experimental results show that the proposed scheme is invisible and robust against common signals processing such as median filtering, sharpening, noise adding, and JPEG compression, etc., and robustagainst desynchronization attacks such as rotation, translation, scaling, row or column removal, cropping, and local random bend, etc.

58 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202372
2022186
2021276
2020387
2019478
2018538