Research on Salt and Pepper Noise Removal Method Based on Adaptive Fuzzy Median Filter

2021 ◽  
Author(s):  
Ping Luo ◽  
Xiaoxiao Zhang ◽  
Zheng Chang ◽  
Wang Liu
Keyword(s):  
Median Filter ◽  
Noise Removal ◽  
Salt And Pepper Noise ◽  
Removal Method ◽  
Adaptive Fuzzy ◽  
Salt And Pepper

scholarly journals Simulated evaluation of new switching based median filter for suppressing SPN and RVIN

2019 ◽  
Vol 15 (2) ◽  
pp. 688 ◽  
Author(s):  
Vorapoj Patanavijit ◽  
Kornkamol Thakulsukanant
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Impulsive Noise ◽  
Median Filter ◽  
Median Filtering ◽  
Salt And Pepper Noise ◽  
Removal Method ◽  
The Past ◽  
Salt And Pepper ◽  
Objective Indicators

<p>In the past two decades, the SPN (salt and pepper noise) suppressing method is worldwide interested researches on computer vision and image processing hence many SPN suppressing methods have been proposed. In general, the primary goal of SPN removal method is the suppressing of SPN in digital images thereby one of the recent effective and powerful SPN suppressing methods is a new switching-based median filtering (NSMF), which is innovated for suppressing high density SPN. Consequently, this paper thoroughly examines its efficiency and constrain of a new switching-based median filtering when this filter is used for contaminated image, which is synthesized by SPN and RVIN (random-value impulsive noise). In these simulations, six well-known images (Lena, Mobile, Pepper, Pentagon, Girl, Resolution) with two impulsive noise classes (SPN and RVIN) are used for measuring the its efficiency and constrain. An evaluation of the efficiency is conducted with many previous methods in forms of subjective and objective indicators.</p>

scholarly journals Fuzzy Based Salt and Pepper Noise Removal Using Adaptive Switching Median Filter

2012 ◽  
Vol 38 ◽  
pp. 2858-2865 ◽  
Author(s):  
V. Thirilogasundari ◽  
V. Suresh babu ◽  
S. Agatha Janet
Keyword(s):  
Median Filter ◽  
Noise Removal ◽  
Salt And Pepper Noise ◽  
Switching Median Filter ◽  
Salt And Pepper

scholarly journals An Improved Method to Remove Salt and Pepper Noise in Noisy Images

2021 ◽  
Author(s):  
Jinder Kaur ◽  
Gurwinder Kaur ◽  
Ashwani Kumar
Keyword(s):  
Signal To Noise Ratio ◽  
Median Filter ◽  
Similarity Index ◽  
Noise Removal ◽  
Mean Value ◽  
Salt And Pepper Noise ◽  
Gray Scale ◽  
Noisy Pixel ◽  
Rgb Images ◽  
Salt And Pepper

In the field of image processing, removal of noise from Gray scale as well as RGB images is an ambitious task. The important function of noise removal algorithm is to eliminate noise from a noisy image. The salt and pepper noise (SPN) is frequently arising into Gray scale and RGB images while capturing, acquiring and transmitting over the insecure several communication mechanisms. In past, the numerous noise removal methods have been introduced to extract the noise from images adulterated with SPN. The proposed work introduces the SPN removal algorithm for Gray scale at low along with high density noise (10\% to 90\%). According to the different conditions of proposed algorithm, the noisy pixel is reconstructed by Winsorized mean or mean value of all pixels except the centre pixel which are present in the processing window. The noise from an image can be removed by using the proposed algorithm without degrading the quality of image. The performance evaluation of proposed and modified decision based unsymmetric median filter (MDBUTMF) is done on the basis of different performance parameters such as Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Image Enhancement Factor (IEF) and Structure Similarity Index Measurement (SSIM).

scholarly journals Adaptive Technique for Salt and Pepper Noise Removal through Functional Link Artificial Neural Network

2019 ◽  
Vol 9 (2) ◽  
pp. 4959-4962
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Median Filter ◽  
Adaptive Method ◽  
Noise Removal ◽  
Least Mean Square ◽  
Salt And Pepper Noise ◽  
Functional Link ◽  
Artificial Neural ◽  
Salt And Pepper

In this paper, an adaptive method for removing salt and pepper noise from images is proposed. A second order difference operator is used to locate the corrupted pixels in images by comparing with a threshold, which is selected adaptively using the image properties. A functional link artificial neural network (FLANN) based method is proposed to set a threshold for each corrupted image for identification of noisy pixels using recursive zero attracting least mean square (RZALMS) as the updating algorithm. Median filter is used to eliminate noise from the detected pixel locations.

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