Reduction of Salt-and-Pepper Noise from Digital Grayscale Image by Using Recursive Switching Adaptive Median Filter

2019 ◽  
pp. 32-47 ◽  
Author(s):  
Aina Qistina Md. Taha ◽  
Haidi Ibrahim
Keyword(s):  
Median Filter ◽  
Grayscale Image ◽  
Salt And Pepper Noise ◽  
Adaptive Median Filter ◽  
Salt And Pepper

An Improved Method of Adaptive Median Filter Based on Noise Density

2014 ◽  
Vol 530-531 ◽  
pp. 403-406 ◽  
Author(s):  
Ping He ◽  
Hong Jian Zhang ◽  
Chao Liu ◽  
Yuan Guo
Keyword(s):  
Euclidean Distance ◽  
Median Filter ◽  
Weighted Average ◽  
Window Size ◽  
Salt And Pepper Noise ◽  
Improved Method ◽  
Adaptive Median Filter ◽  
Noise Density ◽  
Distance Weighted ◽  
Salt And Pepper

To filter salt and pepper noise and protect the texture details of images effectively, an improved method of adaptive median filter is proposed. It can detect the suspicious noise by adjusting the filter window size and adopting the filter algorithm of adaptive texture direction in low density noise area and the filter algorithm of euclidean distance weighted average in high density noise area. Experimental results show that this method has better de-noising and detail-preserving performance.

scholarly journals Ameliorated mean adaptive median filtering algorithm

2019 ◽  
Vol 118 ◽  
pp. 02069
Author(s):  
Hongming Zhang ◽  
Yongping Wang ◽  
Chuang Peng
Keyword(s):  
Median Filter ◽  
Random Noise ◽  
Infrared Image ◽  
Electrical Equipment ◽  
Median Filtering ◽  
Salt And Pepper Noise ◽  
Filtering Algorithm ◽  
Average Value ◽  
Adaptive Median Filter ◽  
Salt And Pepper

Aiming at the problem that the quality of infrared image decreases due to the large amount of random noise in the process of collection and transmission of infrared image of electrical equipment, and the accuracy of automatic detection of electrical equipment decreases, based on the traditional adaptive median filter algorithm, the adaptive median filter is analyzed, which can filter only the salt and pepper noise below 25%. An improved mean adaptive median filtering algorithm is proposed to overcome the shortcomings of wave effect. Firstly, the filtering window is selected according to the decision setting condition, and then it is judged whether the K-mean value near the center point is a noise point, and if so, the window is increased, otherwise the average value is output. Finally, it is judged whether the value of the current pixel point is noise, and if so, the average value is output, otherwise, the current pixel value is output. The experimental results show that the algorithm can effectively filter salt and pepper noise and Gauss noise, while maintaining the image sharpness, and has good filtering performance on PSNR and MSE indicators.

Enhancing the Performance of One Dimensional Median Filter

2019 ◽  
Vol 118 (7) ◽  
pp. 73-76
Author(s):  
Sharanabasappa ◽  
P Ravibabu
Keyword(s):  
Impulse Noise ◽  
Rank Order ◽  
Median Filter ◽  
Filter Method ◽  
Salt And Pepper Noise ◽  
Edge Preservation ◽  
Word Level ◽  
Look Ahead ◽  
Filter Architecture ◽  
Salt And Pepper

Nowadays, during the process of Image acquisition and transmission, image information data can be corrupted by impulse noise. That noise is classified as salt and pepper noise and random impulse noise depending on the noise values. A median filter is widely used digital nonlinear filter  in edge preservation, removing of impulse noise and smoothing of signals. Median filter is the widely used to remove salt and pepper noise than rank order filter, morphological filter, and unsharp masking filter. The median filter replaces a sample with the middle value among all the samples present inside the sample window. A median filter will be of two types depending on the number of samples processed at the same cycle i.e, bit level architecture and word level architecture.. In this paper, Carry Look-ahead Adder median filter method will be introduced to improve the hardware resources used in median filter architecture for 5 window and 9 window for 8 bit and 16 bit median filter architecture.

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