Removal of salt and pepper noise from images using hybrid filter (HF) and fuzzy logic noise detector (FLND)

2018 ◽  
Vol 31 (12) ◽  
Author(s):  
A. Senthil Selvi ◽  
R. Sukumar
Keyword(s):  
Fuzzy Logic ◽  
Salt And Pepper Noise ◽  
Hybrid Filter ◽  
Salt And Pepper

De-noising of images from salt and pepper noise using hybrid filter, fuzzy logic noise detector and genetic optimization algorithm (HFGOA)

2019 ◽  
Vol 79 (5-6) ◽  
pp. 4115-4131 ◽  
Author(s):  
A. Senthil Selvi ◽  
K. Pradeep Mohan Kumar ◽  
S. Dhanasekeran ◽  
P. Uma Maheswari ◽  
S. Ramesh ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Optimization Algorithm ◽  
Genetic Optimization ◽  
Salt And Pepper Noise ◽  
Hybrid Filter ◽  
Salt And Pepper ◽  
Genetic Optimization Algorithm

Hybrid Approach of Efficient Decision-Based Algorithm and Fuzzy Logic for the Removal of High Density Salt and Pepper Noise in Images

2016 ◽  
Vol 25 (10) ◽  
pp. 1650130 ◽  
Author(s):  
P. Karthikeyan ◽  
S. Vasuki
Keyword(s):  
Fuzzy Logic ◽  
Hybrid Approach ◽  
Image Features ◽  
Color Images ◽  
Fuzzy Membership Function ◽  
Salt And Pepper Noise ◽  
Gray Scale ◽  
Processing Window ◽  
Noisy Pixel ◽  
Salt And Pepper

In this paper, this hybrid approach of efficient decision-based scheme and fuzzy logic are proposed for the restoration of gray scale and color images that are heavily corrupted by salt and pepper noise. The processed pixel is examined for 0 or 255; if found true, then it is considered as noisy pixel else not noisy. If found noisy the four neighbors of the noisy pixels are checked for 0 or 255. If all the four neighbors of the corrupted pixel are noisy, the mean of the four neighbors replaces the corrupted pixel. If any of the four neighbors is a non-noisy pixel, the number of corrupted pixels is calculated in the current processing window. If the count is less than three, then the noisy pixel is replaced by an unsymmetrical trimmed median. If the current window has more than three noisy pixels, then unsymmetrical trimmed mean replaces the corrupted pixels. If all the pixels of the current processing window are noisy then instead of enhanced decision-based algorithm, the fuzzy membership function of the window is replaced as output processing pixel. The uncorrupted pixel is left unchanged. The proposed algorithm is tested on various gray scale and color images and found that it gives excellent PSNR, high IEF and lowest MSE. Also it preserves the image features like the edges and color components at higher noise densities. The quality of the results of proposed algorithm is superior when compared to the various existing state-of-the-art methods.

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.

Switching based fuzzy filter for salt-and-pepper noise

2013 ◽  
Vol 32 (5) ◽  
pp. 1293-1295
Author(s):  
Yuan-hua GUO ◽  
Xiao-rong HOU
Keyword(s):  
Salt And Pepper Noise ◽  
Fuzzy Filter ◽  
Salt And Pepper
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