Noise Density Range Sensitive Mean-Median Filter for Impulse Noise Removal

2020 ◽  
pp. 150-162
Author(s):  
Prateek Jeet Singh Sohi ◽  
Nikhil Sharma ◽  
Bharat Garg ◽  
K. V. Arya
Keyword(s):  
Impulse Noise ◽  
Median Filter ◽  
Noise Removal ◽  
Density Range ◽  
Impulse Noise Removal ◽  
Noise Density

scholarly journals A New Spatial Domain Filter for Impulse Noise Removal with Improved Accuracy Based on Multiple Conditions

2020 ◽  
Vol 9 (4) ◽  
pp. 1305-1309
Keyword(s):  
Impulse Noise ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Noise Removal ◽  
Spatial Domain ◽  
Median Filtering ◽  
Impulse Noise Removal ◽  
Noise Density ◽  
Improved Accuracy ◽  
Multiple Conditions

Numerous filtering methods are proposed for Impulse noise removal, it is an important task in the field of image restoration. The familiar spatial domain algorithm to remove impulse noise is Standard Median Filter (SMF). Most of the existing algorithms are based on median filtering and recent algorithms are Modified Hybrid Median Filter (MHMF) and New Modified Hybrid Median Filter (NMHMF). These two are worked up to 20% noise density. In this paper proposed a new` algorithm for impulse noise removal above 20% noise density conditions with different samples of images. The implementation of proposed method compares with known existing methods by comparing Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR).

A new approach for high density saturated impulse noise removal using decision-based coupled window median filter

2013 ◽  
Vol 8 (1) ◽  
pp. 71-84 ◽  
Author(s):  
Vivek Singh Bhadouria ◽  
Dibyendu Ghoshal ◽  
Abul Hasan Siddiqi
Keyword(s):  
Impulse Noise ◽  
Median Filter ◽  
Noise Removal ◽  
High Density ◽  
New Approach ◽  
Impulse Noise Removal

Decision Based Median Filter algorithm using Resource Optimized FPGA to Extract Impulse Noise

2014 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Rutuja Nandkumar Kulkarni ◽  
Pradip C Bhaskar
Keyword(s):  
Impulse Noise ◽  
Median Filter ◽  
Noise Removal ◽  
Mean Value ◽  
Linear Filter ◽  
Noise Detection ◽  
Object Boundary ◽  
Typical Application ◽  
Impulse Noise Removal ◽  
Noisy Pixel

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.

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