Impulse noise detection and removal using multiple weighted median filters

2011 ◽  
Author(s):  
Dimitrios Charalampidis ◽  
Naga R. Vayuvegula
Keyword(s):  
Impulse Noise ◽  
Noise Detection ◽  
Median Filters ◽  
Weighted Median ◽  
Weighted Median Filters ◽  
Impulse Noise Detection

PERFORMANCE BOUNDARIES OF OPTIMAL WEIGHTED MEDIAN FILTERS

2004 ◽  
Vol 04 (02) ◽  
pp. 157-182 ◽  
Author(s):  
RASTISLAV LUKAC
Keyword(s):  
Order Statistic ◽  
Impulse Noise ◽  
Nonlinear Filter ◽  
Edge Preservation ◽  
Sign Function ◽  
Median Filters ◽  
Weighted Median ◽  
Statistic Theory ◽  
Weighted Median Filters ◽  
Optimization Schemes

This paper focuses on image filtering using weighted median (WM) filters, a nonlinear filter class taking advantages of the robust order-statistic theory and capability to adapt a filter behavior for a variety of statistics related to the desired signals and the noise distributions. The main contribution of the paper is the analysis of the four WM optimization schemes, namely genetic WM optimization, non-adaptive WM optimization algorithm and adaptive WM filtering utilizing the linear and the sigmoidal approximation of the sign function. The analysis is done by extensive simulations, in which several features such as noise reduction, edge preservation, error estimation and dependence of error criteria on the degree of the impulse noise corruption, are examined.

Impulse Noise Detection and Removal Method Based on Modified Weighted Median

2020 ◽  
Vol 8 (2) ◽  
pp. 38-53
Author(s):  
Ashpreet ◽  
Mantosh Biswas
Keyword(s):  
Impulse Noise ◽  
Noise Suppression ◽  
Extreme Values ◽  
Median Filter ◽  
Noise Removal ◽  
Filter Method ◽  
Noise Detection ◽  
Median Filters ◽  
Removal Method ◽  
Weighted Median

Impulse noise generally occurs because of bit errors in progression of image acquisition and transmission. It is well known that median filtering method is an impulse noise removal method. Lots of modified median filters have been proposed in the last decades to improve the methods for noise suppression and detail preservation, which have their own deficiencies while identifying and restoring noise pixels. In this article, after deeply analyzing the reasons, such as decreased noise detection and noise removal accuracy that forms the basis of the deficiencies, this article proposes a modified weighted median filter method for color images corrupted by salt-and-pepper noise. In this method, a pixel is classified into either “noise free pixel” or “noise pixel” by checking the center pixel in the current filtering window with the extreme values (0 or 255) for an 8-bit image using noise detection step. Directional differences and the number of “good” pixels in the current filtering window modify the detected noise pixels. Simulation effects on considered test images reveal the proposed method to be improved over state-of-the-art de-noising methods in terms of PSNR and SSIM with pictorial comparative analysis.

Weighted Median Filters for Multichannel Signals

2006 ◽  
Vol 54 (11) ◽  
pp. 4271-4281 ◽  
Author(s):  
Y. Li ◽  
G.R. Arce ◽  
J. Bacca
Keyword(s):  
Median Filters ◽  
Multichannel Signals ◽  
Weighted Median ◽  
Weighted Median Filters
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