Topic
Median filter
About: Median filter is a research topic. Over the lifetime, 12479 publications have been published within this topic receiving 178253 citations.
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Papers
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TL;DR: Experimental results show that the images filtered with the proposed method contain less noisy pixels than those obtained through the vector median filter.
Abstract: This paper describes a new filter for impulse noise reduction in colour images which is aimed at improving the noise reduction capability of the classical vector median filter. The filter is inspired by the application of a vector marginal median filtering process over a selected group of pixels in each filtering window. This selection, which is based on the vector median, along with the application of the marginal median operation constitutes an adaptive process that leads to a more robust filter design. Also, the proposed method is able to process colour images without introducing colour artifacts. Experimental results show that the images filtered with the proposed method contain less noisy pixels than those obtained through the vector median filter.
39 citations
01 Dec 2013
TL;DR: An improved algorithm fusing the enhanced Lee filter and median filter based on spatial filtering of SAR image speckle has a good performance in preserving edges and details while filtering images.
Abstract: Speckle noise usually occurs in synthetic aperture radar (SAR) images , and SAR data is processed coherently. Speckle filters commonly are adaptive filters using local statistics such as mean and standard deviation, such as the Lee and its enhanced filters and median filter. They adapt the filter coefficients based on data within a fixed moving window, and this brings in contradiction between the quality of speckle noise suppression and the capability of preserving image details. The Lee filter decreases speckle noise well in homogeneous regions, and the enhanced filter performs well both in the homogeneous and heterogeneous areas. But it does not effectively maintain image edges and details, while depressing SAR image noise. The median filter does well in decreasing impulse noise. In this paper, we propose an improved algorithm fusing the enhanced Lee filter and median filter based on spatial filtering of SAR image speckle. The experiment proves it has a good performance in preserving edges and details while filtering images.
39 citations
TL;DR: In this article, a pre-filtering technique is used to reduce noise in ultrasound pixel images by shrinking initial image data and processing the shrunken image with known segmentation-based filtering techniques that identify and differentially process structures within the image.
Abstract: In ultrasound imaging, acquired images are corrupted by slowly varying multiplicative non-uniformity. When the image is corrected for non-uniformity alone, noise in the dark regions of the original image becomes multiplicatively enhanced, thereby providing an unnatural look to the image. A pre-filtering technique is used to reduce noise in ultrasound pixel images by shrinking initial image data and processing the shrunken image with known segmentation-based filtering techniques that identify and differentially process structures within the image. The segmentation is based on both gradient threshold and the distance from the near field of the ultrasound image. This modification selectively suppresses near-field artifacts. After processing, the shrunken image is enlarged to the dimensions of the initial data and then blended with the initial image to form the final image. During blending, a small predetermined fraction of intensity-dependent, uniform random noise is added to the non-structure region pixels whose intensities are above a pre-specified intensity threshold, to mitigate ultrasound speckles while leaving non-echogenic regions undisturbed.
39 citations
01 Dec 2017
TL;DR: In this paper, performance evaluation of the of MRI image de-noising techniques is provided and a new method is proposed which modifies the existing median filter by adding features.
Abstract: For the study of anatomical structure and image processing of MRI medical images techniques of noise removal have become an important practice in medical imaging application. In medical image processing, precise images need to be obtained to get accurate observations for the given application. The goal of any de-noising technique is to remove noise from an image which is the first step in any image processing. The noise removal method should be applied watchful manner otherwise artefacts can be introduced which may blur the image. In this paper, performance evaluation of the of MRI image de-noising techniques is provided. The techniques used are namely the median and Gaussian filter, Max filter [11], Min filter [11], and Arithmetic Mean filter [8]. All the above filters are applied on MRI brain and spinal cord images and the results are noted. A new method is proposed which modifies the existing median filter by adding features. The experimental result of the proposed method is then analyzed with the other three image filtering algorithms. The output image efficiency is measured by the statistical parameters like root mean square error (RMSE), signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR).
39 citations
TL;DR: A novel adaptive median-based filter, called the partition fuzzy median (PFM) filter, which achieves its effect through a summation of the weighted output of the median filter and the related weighted input signal.
39 citations