Topic
Median filter
About: Median filter is a research topic. Over the lifetime, 12479 publications have been published within this topic receiving 178253 citations.
Papers published on a yearly basis
Papers
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Patent•
07 Sep 2004TL;DR: In this paper, a nonlinear filter such as a moving median filter is applied to individual mass chromatograms, plots of ion abundance versus retention time for each detected mass-to-charge ratio, and the filtered chromatogram are combined to form a filtered total ion current.
Abstract: High-intensity, spiked noise is reduced in chromatography-mass spectrometry data by applying a nonlinear filter such as a moving median filter to the data. The filter is applied to individual mass chromatograms, plots of ion abundance versus retention time for each detected mass-to-charge ratio, and the filtered chromatograms are combined to form a filtered total ion current chromatogram. Standard linear filters are not effective for reducing noise in liquid chromatography-mass spectrometry (LC-MS) data because they assume a normal distribution of noise. LC-MS noise, however, is not normally distributed.
43 citations
Patent•
12 Apr 2006TL;DR: In this article, a method of removing noise by using a change in an activity pattern is proposed. But the method is not suitable for the case where noise components exist in different frequency bands and different filters for removing noise are stored according to each activity pattern.
Abstract: A noise removal method and system using a change in activity pattern, in which it is recognized that noise components exist in different frequency bands and different filters for removing noise are stored according to each activity pattern, thereby optimally removing the noise components. A method of removing noise by using a change in an activity pattern includes: recognizing an activity pattern of the subject using an activity sensor; sensing a first bio signal corresponding to the activity pattern from the subject using an electric potential sensor; recognizing a noise generation pattern according to the activity pattern by analyzing a noise component for each section of the first bio signal; selecting filter information for each section according to the noise generation pattern; storing the filter information selected for each section in association with the activity pattern; and removing noise from a second bio signal sensed from the subject by applying the stored filter information.
43 citations
TL;DR: The proposed approach combines color edge detection, bilateral noise filter, and edge enhancement based on suitable color spaces and shows that the proposed approach can effectively reduce the noise while preserving and enhancing edges.
Abstract: Removing noise while preserving and enhancing edges is one of the most fundamental operations of image/video processing. When taking pictures with digital cameras, it is frequently found that the color images are corrupted by miscellaneous noise and, hence, noise filtering is necessary. The difficulty is that usually the filtering will reduce the sharpness of the image. On the other hand, optical lens imperfections are usually equivalent to spatial low pass filters and tend to result in blurred images. It is customary to apply edge enhancement algorithm on the image in order to improve the sharpness, but this process usually increase the noise level as a by-product. In this paper, we present a new integrated approach to address these issues. The proposed approach combines color edge detection, bilateral noise filter, and edge enhancement based on suitable color spaces. The experimental results show that the proposed approach can effectively reduce the noise while preserving and enhancing edges.
43 citations
TL;DR: Examination of image filtering operations based on the local intensity histogram finds the ‘truncated median’ filter to be highly effective both for image enhancement and for introducing a certain amount of noise suppression.
43 citations
TL;DR: The proposed algorithm has the advantage of preventing from prematurity and fast convergence speed, and a smaller MAE for all noise levels is achieved and much detailed information of the images is preserved.
43 citations