An enhanced decision based Unsymmetric Trimmed Median Filter for removal of high density salt and papper noise

2015 ◽  
Author(s):  
Shruti Singh ◽  
Anil Kumar Tiwari
Keyword(s):  
Median Filter ◽  
High Density

An Effective Noise Adaptive Median Filter for Removing High Density Impulse Noises in Color Images

2016 ◽  
Vol 6 (2) ◽  
pp. 611 ◽  
Author(s):  
S. Abdul Saleem ◽  
T. Abdul Razak
Keyword(s):  
Median Filter ◽  
Color Images ◽  
High Density ◽  
Correct Selection ◽  
Median Filtering ◽  
Filtering Algorithms ◽  
Image Metrics ◽  
Quantitative Image ◽  
Degraded Images ◽  
Image Details

Images are normally degraded by some form of impulse noises during the acquisition, transmission and storage in the physical media. Most of the real time applications usually require bright and clear images, hence distorted or degraded images need to be processed to enhance easy identification of image details and further works on the image. In this paper we have analyzed and tested the number of existing median filtering algorithms and their limitations. As a result we have proposed a new effective noise adaptive median filtering algorithm, which removes the impulse noises in the color images while preserving the image details and enhancing the image quality. The proposed method is a spatial domain approach and uses the 3×3 overlapping window to filter the signal based on the correct selection of neighborhood values to obtain the effective median per window. The performance of the proposed effective median filter has been evaluated using MATLAB, simulations on a both gray scale and color images that have been subjected to high density of corruption up to 90% with impulse noises. The results expose the effectiveness of our proposed algorithm when compared with the quantitative image metrics such as PSNR, MSE, RMSE, IEF, Time and SSIM of existing standard and adaptive median filtering algorithms.

scholarly journals High Density Impulse Noise Removal using Advanced Median Filter for Preserving Image Quality Metrics

2019 ◽  
Vol 8 (4) ◽  
pp. 11909-11914
Keyword(s):  
Image Quality ◽  
Impulse Noise ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Noise Removal ◽  
Quality Metrics ◽  
High Density ◽  
Image Quality Metrics ◽  
Neighboring Pixel ◽  
Salt And Pepper

In this work, a procedure to remove the high density salt and pepper noise from a corrupted image is developed and to compare the output image with the original image through the image quality metrics. As a common practice the corrupted pixels are replaced by the median of neighboring pixel values by considering a constant number of neighboring pixels. But in this proposed method the corrupted pixels are identified and are replaced by the median of the neighboring pixel values which are adjustable, to preserve and improve the image quality metrics. This method makes a comparison between the corrupted and uncorrupted pixels and performs the median filtering process only on the corrupted ones. In this work a 3x3, 5x5 and 7x7 square neighborhood are used. The output images are observed with low neighborhood as well as high neighborhood pixel values. The calculation of PSNR (Peak Signal to Noise Ratio) and MSE (Mean square error) value for each dimension with different percentages are considered for the comparative analysis

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