Salt and pepper noise filtering algorithm based on connectivity detection

2020 ◽  
Vol 35 (2) ◽  
pp. 167-172
Author(s):  
马逸东 MA Yi-dong ◽  
周顺勇 ZHOU Shun-yong
Keyword(s):  
Noise Filtering ◽  
Salt And Pepper Noise ◽  
Filtering Algorithm ◽  
Salt And Pepper

scholarly journals Reconstruction of Corrupted Image From Salt And Pepper Noise From Median Filter

2012 ◽  
pp. 4-6
Author(s):  
Vishal Gautam ◽  
Tarun Varma
Keyword(s):  
Median Filter ◽  
Median Filtering ◽  
Salt And Pepper Noise ◽  
Filtering Algorithm ◽  
Noise Density ◽  
Mean Filter ◽  
Salt And Pepper ◽  
Image Details ◽  
Lower Noise ◽  
Better Than

- Inthis paper,we propose an improved median filtering algorithm. Here, we introduced salt and pepper noise for the image corruption and reconstruct original image using different filters i.e. mean, median and improved median filter. The performance of improved median filter is good at lower noise density levels.The mean filter suppresses little noise and gets the worst results.The experimental resultsshow that our improved median filter is better than previousmedian filterfor lower noise density (upto 60%). It removes most of the noises effectively while preserving image details very well.

Salt and pepper noise filtering algorithms based on switch two-stage detection

2019 ◽  
Vol 34 (1) ◽  
pp. 74-80
Author(s):  
郑 亮 ZHENG Liang ◽  
方恩印 FANG En-yin ◽  
朱 明 ZHU Ming
Keyword(s):  
Noise Filtering ◽  
Salt And Pepper Noise ◽  
Two Stage ◽  
Filtering Algorithms ◽  
Salt And Pepper

An Image Filtering Algorithm for Removing Mixed Noise

2013 ◽  
Vol 433-435 ◽  
pp. 383-388 ◽  
Author(s):  
Mao Xiang Chu ◽  
An Na Wang ◽  
Rong Fen Gong
Keyword(s):  
Gaussian Noise ◽  
Weighting Function ◽  
Median Filter ◽  
Bilateral Filter ◽  
Salt And Pepper Noise ◽  
Filtering Algorithm ◽  
Noise Simulation ◽  
Mixed Noise ◽  
Local Edge ◽  
Salt And Pepper

In order to remove salt-and-pepper noise and Gaussian noise in image, a novel filtering algorithm is proposed in this paper. The novel algorithm can preserve image edge details as much as possible. Firstly, five-median-binary code (FMBC) is proposed and used to describe local edge type of image. Secondly, median filter algorithm is improved to remove salt-and-pepper noise by using FMBC. Then, local enhanced bilateral filter with FMBC and a new type of exponential weighting function is used to remove Gaussian noise. Simulation results show that the algorithm proposed in this paper is very effective not only in filtering mixed noise but also in preserving edge details.

scholarly journals Robust Estimators in Fuzzy Logic Cellular-Automata Salt and Pepper Noise Filtering

2015 ◽  
Vol 15 (1) ◽  
pp. 6402-6407
Author(s):  
Nicholas LaVigne ◽  
Yusuf Bilgic
Keyword(s):  
Cellular Automata ◽  
Computational Algorithms ◽  
Noise Filtering ◽  
Salt And Pepper Noise ◽  
High Contrast ◽  
Nonparametric Estimators ◽  
New Methods ◽  
Sharp Edges ◽  
Salt And Pepper ◽  
Symmetric Patterns

In order to increase the performance of computational algorithms in terms of efficiency of estimators, we tested new nonparametric estimators in fuzzy and cellular automata models.  In particular, image de-noising algorithms exist to restore digital images corrupted by impulse noise.  These algorithms may do poorly in many common cases, for example, when high contrast and sharp edges lead to outliers, spikes, or non-symmetric patterns for neighborhing pixels.  This would stem from the choices of estimators in the algorithms. We investigated new nonparametric estimators and compared to existing methods in simulation study. We detected better performances of our new methods under various situations.

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.

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