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

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).

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Adaptive Right Median Filter for Salt-and-Pepper Noise Removal

Uluslararası Muhendislik Arastirma ve Gelistirme Dergisi ◽

10.29137/umagd.495904 ◽

2019 ◽

pp. 542-550 ◽

Cited By ~ 3

Author(s):

Uğur Erkan ◽

Levent Gökrem ◽

Serdar Enginoğlu

Keyword(s):

Median Filter ◽

Noise Removal ◽

Salt And Pepper Noise ◽

Salt And Pepper

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

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.b3959.129219 ◽

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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