An efficient implementation of switching median filter with boundary discriminative noise detection for image corrupted by impulse noise

2011 ◽  
Vol 6 (26) ◽  
Author(s):  
Haidi Ibrahim
Author(s):  
Pavel S. Zvonarev ◽  
Ilia V. Apalkov ◽  
Vladimir V. Khryashchev ◽  
Irina V. Reznikova

Author(s):  
Rutuja Nandkumar Kulkarni ◽  
Pradip C Bhaskar

Median filter is a non-linear filter used in image processing for impulse noise removal. It finds its typical application in the situations where edges are to be preserved for higher level operations like segmentation, object recognition etc. This paper presents an accurate and efficient noise detection and filtering algorithm for impulse noise removal. The algorithm includes two stages: noise detection followed by noise filtering. The proposed algorithm replaces the noisy pixel by using  median value when other pixel values, 0’s or 255’s are present in the selected window and when all the pixel values are 0’s and 255’s then the noise pixel is replaced by mean value of all the elements present in the selected window. Similarly algorithm checks for five different conditions to preserve image details, object boundary in high level of noise densities. This median filter was designed, simulated and synthesized on the Xilinx family of FPGAs (XC3S500E of Spartan-3E). The VHDL was used to design the above 2-D median filter using ISE (Xilinx) tool & tested & compared for different grayscale images.


2013 ◽  
Vol 411-414 ◽  
pp. 1546-1551 ◽  
Author(s):  
Zhong Tao Qiao ◽  
Feng Qi Gao ◽  
Guang Long Wang ◽  
Liang Liang Chang

In image digitization and transmission, images often suffer contamination inevitably. The noises in images often consist of Gaussian noise and impulse noise. The common denoising algorithms are capable of removing single one of them. In order to remove those two types of noise, a composite algorithm is proposed. Firstly, based on median filter, an impulse noise detection algorithm is used to filter impulse noise. Secondly, adaptive directional lifting wavelet (ADL) and normal lifting wavelet is combined to suppress noise from image signal and protect the texture edge from loss simultaneously. Meanwhile an improved half-soft threshold is used for normal lifting wavelet. At last, simulations show that this technology can suppress Gaussian and impulse noise in image efficiently.


2008 ◽  
Vol 54 (4) ◽  
pp. 1956-1961 ◽  
Author(s):  
Kenny Toh ◽  
Haidi Ibrahim ◽  
Muhammad Mahyuddin

2010 ◽  
Vol 6 (4) ◽  
pp. 613-624 ◽  
Author(s):  
A. Nasimudeen ◽  
Madhu S. Nair ◽  
Rao Tatavarti

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