A Repeated Median Filtering Method for Denoising Mammogram Images

An X-ray inspection machine image detection system is designed by making use of the software Visual C++ 6.0, in which a lot of noise in the X-ray image are filted out by using corrosion algorithms and median filtering method. A analysis software of the bridging of the solderjoints, weld situation is designed,which can real-time display and zoom the image of solder joint inspection, and can alarm.

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A Median Filtering Method for Pulse Noise Detection

Proceedings of the 2017 International Conference on Social science, Education and Humanities Research (ICSEHR 2017) ◽

10.2991/icsehr-17.2017.24 ◽

2017 ◽

Author(s):

Zhang Yamei

Keyword(s):

Median Filtering ◽

Noise Detection ◽

Pulse Noise ◽

Filtering Method

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An Improved Median Filtering Method and its Applications in Features Extraction of GRIN Lens EndImage

Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016) ◽

10.2991/ifmca-16.2017.21 ◽

2017 ◽

Author(s):

Song-Lin Wu ◽

Bo Zhang ◽

Min Zhang

Keyword(s):

Features Extraction ◽

Median Filtering ◽

Filtering Method ◽

Grin Lens

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The Median Filtering of Digital Image Based on MATLAB

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.318.67 ◽

2013 ◽

Vol 318 ◽

pp. 67-70 ◽

Cited By ~ 1

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.

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A Study of the De-Noising Methods for Cotton Fabric Rubbing Sound Signal

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.815.905 ◽

2013 ◽

Vol 815 ◽

pp. 905-909

Author(s):

Hong Shan Wang ◽

Wei Lin Xu

Keyword(s):

Cotton Fabric ◽

Noise Signal ◽

Sound Signal ◽

Median Filtering ◽

Wavelet Method ◽

Practical Applications ◽

Filtering Method ◽

Clear Signal

In order to get clear cotton rustling sound signal, which will be analyzed to provide information at a certain stage of fabric processing for developing cotton products, before analysis of the data, it is the need for de-noising processing. The two de-noising methods, the median filtering method and the wavelet method are proposed in this paper. Their principles and algorithms are described. The cotton sound signals are exposed to interference and influence of some kinds of noise signal in the process of the data measured. So in practical applications, the two de-noising methods are used to process cotton rustling sound. The results of the process show the methods of processing the cotton sound signal are effective. The clear signal is getting to the next research.

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A Median Filtering Algorithm Based on Extremum Detection

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.889-890.1099 ◽

2014 ◽

Vol 889-890 ◽

pp. 1099-1102 ◽

Cited By ~ 2

Author(s):

Liang Yan ◽

Gao Yan ◽

Qin Xia Zhao

Keyword(s):

Recovery Process ◽

Noise Removal ◽

Experimental Results ◽

Noise Filtering ◽

Median Filtering ◽

Noise Detection ◽

False Detection ◽

Filtering Method ◽

Filtering Algorithm ◽

Two Stages

In this paper a improved algorithm of median filtering based on extremum detection is introduced. According to the deficiencies of the extreme median filtering method in the two stages of noise detection and noise filtering, Adds a false detection noise pixel gray value correction recovery process. Experimental results show that the algorithm in this paper are superior than traditional median filtering algorithm and some improved image filtering algorithm in noise removal and edge retention.

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