scholarly journals Effect of Matrix Size in Affecting Noise Reduction Level of Filtering

2018 ◽  
Author(s):  
Andysah Putera Utama Siahaan ◽  
Solly Aryza ◽  
Muhammad Dharma Tuah Putra Nasution ◽  
Darmawan Napitupulu ◽  
Darmawan Napitupulu ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Noise Reduction ◽  
Nonlinear Filtering ◽  
Median Filter ◽  
Median Filtering ◽  
Matrix Size ◽  
Matrix Block ◽  
The Matrix ◽  
Pixel Value

Improved image quality needs to be done to improve data processing on the image. This quality improvement can be made by doing masking technique. Median Filter is one technique to enhance the quality of an image in a particular space. Median filtering improves the image by specifying a specific pixel from its neighboring pixels. The median filtering calculation uses a matrix block with an odd number. Each matrix block will have a middle value after the pixel values have regularly been sorted. This method is included in the category of nonlinear filtering. With the median filtering, the output pixel value is determined by the median of the specified mask environment. Median Filter has different results when using different matrix sizes as well. The results of this process can determine how gentle the result of noise reduction. In general, the larger the size of the matrix, the higher the blurriness of an image.

scholarly journals Effect of matrix size in affecting noise reduction level of filtering

2018 ◽  
Vol 7 (3) ◽  
pp. 1272 ◽  
Author(s):  
Khairul . ◽  
Rian Farta Wijaya ◽  
Andysah Putera Utama Siahaan ◽  
Solly Aryza ◽  
Fitria Nova Hulu ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Noise Reduction ◽  
Nonlinear Filtering ◽  
Median Filter ◽  
Median Filtering ◽  
Matrix Size ◽  
Matrix Block ◽  
The Matrix ◽  
Pixel Value

Improved image quality needs to be done to improve data processing on the image. This quality improvement can be made by doing masking technique. Median Filter is one technique to enhance the quality of an image in a particular space. Median filtering improves the image by specifying a specific pixel from its neighboring pixels. The median filtering calculation uses a matrix block with an odd number. Each matrix block will have a middle value after the pixel values have regularly been sorted. This method is included in the category of nonlinear filtering. With the median filtering, the output pixel value is determined by the median of the specified mask environment. Median Filter has different results when using different matrix sizes as well. The results of this process can determine how gentle the result of noise reduction. In general, the larger the size of the matrix, the higher the blurriness of an image.   

PENERAPAN METODE ADAPTIVE MEDIAN FILTER UNTUK MEREDUKSI NOISE PADA CITRA X-RAY

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Wika Elsa Pratiwi ◽  
Fince Tinus Waruwu
Keyword(s):  
Median Filter ◽  
Filter Method ◽  
X Ray ◽  
Adaptive Median Filter ◽  
The Matrix ◽  
Image Noise Reduction ◽  
Pixel Value ◽  
Pixel Image ◽  
Maximum Minimum

The problem often faced by radiologists in analyzing thorax fractures through manual x-ray images and requiring a longer time to study the image and radiologists also often have difficulty reading x-ray images that have noise when shooting x-ray and can lead to difficulties in diagnosis. The adaptive median filter method is a suitable problem-solving technique. In the improvement of the quality of the x-ray image, the x-ray image must first be converted into the pixel image value, to get the pixel value from the x-ray image. -ray then determine the matrix value to get the maximum, minimum, median and pixel coordinate values. Then determine whether the pixel value will be replaced with a median value, if not noise then the pixel value is not replaced. The end result of this system is in the form of design in reducing noise on x-ray imagery which is used as an aid in analyzing x-ray images. This system will help radiologists in reading images.Keywords: X-ray image, noise reduction, adaptive median filter

scholarly journals IMPLEMENTATION OF MODIFIED MEDIAN FILTERING ALGORITHM FOR SALT & PEPPER NOISE REDUCTION ON IMAGE

2017 ◽  
Author(s):  
Robbi Rahim ◽  
Ali Ikhwan
Keyword(s):  
Image Quality ◽  
Noise Reduction ◽  
Special Technique ◽  
Median Filtering ◽  
Filtering Algorithm ◽  
Analog Signals ◽  
Pixel Value ◽  
The Mean ◽  
Spatial Window ◽  
Mean Filtering

Noise is one form of issue in the image, salt & pepper noise is the kind of noise that can be made using a special technique or also due to the conversion from analog signals to digital, the noise can be improved by using algorithms such as the mean filtering, the mid-point filtering and median filtering, median filtering algorithm is widely used for repair image quality, this article will discuss the modification of the median filtering to improve noise in the image by taking the average of neighboring pixels by 2 points from the value of the center clockwise, the value is taken to be processed to retrieve the value of the middle and then the overall result value will be divided to replace the center pixel value 3x3 spatial window.

scholarly journals Research on Yarn Diameter and Unevenness Based on an Adaptive Median Filter Denoising Algorithm

2020 ◽  
Vol 28 (1(139)) ◽  
pp. 36-41
Author(s):  
Xiao Wang ◽  
Ru-Meng Hou ◽  
Xiao-Yan Gao ◽  
Bin-Jie Xin
Keyword(s):  
Detection Method ◽  
Median Filter ◽  
Morphological Processing ◽  
Median Filtering ◽  
Yarn Diameter ◽  
Testing Data ◽  
Adaptive Median Filter ◽  
Image Separation ◽  
Image Acquisition System

In this paper an adaptive median filtering denoising algorithm is proposed to measure yarn diameter and its unevenness. Images of nine different yarn samples were captured using one set of a self-developed yarn image acquisition system. Image separation of the background and yarn sections was conducted using a combination of adaptive median filtering, adaptive threshold segmentation and morphological processing. The noise-free yarn image was used for diameter detection of the subsequent yarn image and the discrimination of the yarn unevenness. Experimental results show that the testing data of yarn unevenness detection based on the adaptive median filter denoising algorithm is very consistent with the data using the traditional method. It is proved that the yarn detection method proposed, based on an adaptive median filter denoising algorithm, is feasible. It can be used to calculate yarn diameter accurately and measure yarn unevenness efficiently, so as to determine the quality of yarn appearance objectively.

scholarly journals CONSTANT TIME SCANNING AND BETTER EDGE PRESERVATION FOR BETTER PERFORMING AND QUALITY OF MEDIAN FILTER

2012 ◽  
pp. 114-116
Author(s):  
RITWIK SHARMA ◽  
SHUBHAM HARNAL
Keyword(s):  
Image Processing ◽  
Median Filter ◽  
Median Filtering ◽  
Edge Preservation ◽  
Median Filters ◽  
Novel Approach ◽  
Time Scanning ◽  
The Cost ◽  
Salt And Pepper

The median filter is an important filter in many image processing algorithms and especially in removal of salt and pepper noise. Traditional median filters either focus on improving the performance or the quality of the median filtering. Generally, the methods which optimize performance do so at the cost of quality and vice-versa. In this paper a novel approach to median filtering is presented providing both better performance and quality without sacrificing either. The analysis is presented with respect to image processing and the results obtained are presented in tabular form.

scholarly journals A Case Study to Improve the Quality of Median Filter

2021 ◽  
Vol 10 (11) ◽  
pp. 19-28
Author(s):  
Ziad A. Alqadi ◽  
Mohamad Tariq Barakat
Keyword(s):  
Noise Reduction ◽  
Digital Image ◽  
Median Filter ◽  
Reduction Process ◽  
Research Paper ◽  
Quality Factors ◽  
High Noise ◽  
Negative Effect

The median filter is used to reduce the effect of noise, but it treats all pixels, whether they are noise points or not, which negatively affects many non-noise values in the digital image, and the negative effect increases as the noise ratio increases. In order to get rid of some of the disadvantages of the median filter, we will present in this research paper a detailed study that works on treating the unaffected and infected pixels so that this treatment leads to improving the performance of the filter by raising the values of the quality factors of the filter. The improvements added to the median filter will raise the efficiency of the noise reduction process, especially for high noise ratios.

The Median Filtering of Digital Image Based on MATLAB

2013 ◽  
Vol 318 ◽  
pp. 67-70 ◽  
Author(s):  
Hai Qiang Wang ◽  
Xian Ge Sun
Keyword(s):  
Image Processing ◽  
Adaptive Filter ◽  
Digital Image ◽  
Nonlinear Filtering ◽  
Noise Intensity ◽  
Median Filter ◽  
Low Noise ◽  
Median Filtering ◽  
Filtering Method ◽  
Filtering Technique

In the processing of image de-noising, median filtering is a more common nonlinear filtering technique. In this paper, we used the image processing toolbox in the matlab and the adaptive filter program by ourselves. The noise in different intensity of image is reduced. This paper discussed the problem that how we choice of the filtering method under different noise intensity. The results show that median filter can realize effective filter under low noise intensity, if the noise intensity is excessively large, the adaptive filter having a more ideal filtering result than that of standard median filter.

scholarly journals Experimental Study of Modified Multilevel Median Filter for Noise Reduction

2019 ◽  
pp. 135-139 ◽  
Author(s):  
Eko Hariyanto ◽  
Andysah Putera Utama Siahaan ◽  
Solly Aryza
Keyword(s):  
Experimental Study ◽  
Noise Reduction ◽  
Image Enhancement ◽  
Digital Image ◽  
Digital Images ◽  
Median Filter ◽  
Experiment Study ◽  
Digital Image Enhancement

Digital image enhancement is efforts to improve the quality of a declining image and one of the causes of the decline in the quality of digital images is the emergence of spots called noise. Median filter is one method that is widely used and developed to digital images noise reduction. In this paper, we conducted an experiment study to reduce noise using a standard multilevel median filter and a modified multilevel median filter. Further, we measured the images filtered quality using MSE and PNSR to find out the advantages of both methods.

A Combination Approach to Noise Reduction in Digital Image Processing

2013 ◽  
Vol 278-280 ◽  
pp. 1359-1365
Author(s):  
Jing Dong ◽  
Zhi Chai ◽  
Ke Wen Xia
Keyword(s):  
Noise Reduction ◽  
Digital Image ◽  
Gaussian Noise ◽  
Median Filter ◽  
The Other ◽  
Median Filtering ◽  
Mean Filter ◽  
The Mean ◽  
Combination Approach ◽  
Mean Filtering

In order to reduce Gaussian and Salt & Pepper noises, a combination approach to noise reduction is presented by combining the median filter with the mean filter. The detail simulations show that the mode which the median filtering first and then the mean filtering is superior to that of the simply single filtering, or the mean filtering first and then the median filtering when the image obviously contain the Salt & Pepper noise. On the other hand, it is not necessarily the optimal scheme to use the mode which the mean filtering first and then the median filtering when the digital image obviously contains the Gaussian noise.

Filtering Algorithm for Removing Image Impulse Noise

2014 ◽  
Vol 543-547 ◽  
pp. 2817-2820
Author(s):  
Li Hua Sun ◽  
En Liang Zhao ◽  
Bao Yang Yu
Keyword(s):  
Numerical Experiments ◽  
Small Area ◽  
Impulse Noise ◽  
Median Filter ◽  
Median Filtering ◽  
Effective Algorithm ◽  
Signal To Noise ◽  
Edge Information ◽  
Filtering Algorithm ◽  
Pixel Value

The paper is devoted to put forward an effective algorithm for removing image impulse noise by improving the traditional median filter. The following approaches are developed in this paper. First, in a small area all the pixels are separated into signal pixels and suspicious noise pixels making use of the extremum and median filtering algorithm .Then suspicious noise pixels are further identified the signal pixels and noise pixels around pixels. If a pixel value is a noise pixel, it will be processed by median filter. A signal pixel will retain the original pixel value. The numerical experiments show that compared with traditional median filter , the details and edge information of the original image are retained when the new algorithm is used , Comparing with extremum median filter algorithm, the ratio of peak signal to noise can increase up to 2.94 at most. As a result, it is an effective algorithm for image denoising that can eliminate impulse noise in the image effectively.

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