Multi scale sequential median filter for high percentage impulsive noise removal

2017 ◽  
Author(s):  
Dongjie Tan ◽  
Haoyin Lv
Keyword(s):  
Impulsive Noise ◽  
Median Filter ◽  
Noise Removal ◽  
Multi Scale

scholarly journals Decision-Based Marginal Total Variation Diffusion for Impulsive Noise Removal in Color Images

2017 ◽  
Vol 2017 ◽  
pp. 1-18
Author(s):  
Hongyao Deng ◽  
Qingxin Zhu ◽  
Xiuli Song
Keyword(s):  
Total Variation ◽  
Color Image ◽  
Impulsive Noise ◽  
Median Filter ◽  
Noise Removal ◽  
Color Images ◽  
Natural Image ◽  
Noise Characteristics ◽  
Switching Median Filter ◽  
Vector Median

Impulsive noise removal for color images usually employs vector median filter, switching median filter, the total variation L1 method, and variants. These approaches, however, often introduce excessive smoothing and can result in extensive visual feature blurring and thus are suitable only for images with low density noise. A marginal method to reduce impulsive noise is proposed in this paper that overcomes this limitation that is based on the following facts: (i) each channel in a color image is contaminated independently, and contaminative components are independent and identically distributed; (ii) in a natural image the gradients of different components of a pixel are similar to one another. This method divides components into different categories based on different noise characteristics. If an image is corrupted by salt-and-pepper noise, the components are divided into the corrupted and the noise-free components; if the image is corrupted by random-valued impulses, the components are divided into the corrupted, noise-free, and the possibly corrupted components. Components falling into different categories are processed differently. If a component is corrupted, modified total variation diffusion is applied; if it is possibly corrupted, scaled total variation diffusion is applied; otherwise, the component is left unchanged. Simulation results demonstrate its effectiveness.

scholarly journals An Empirical Evaluation of the Parameters of Trilateral Filter for Noise Removal Implementation on Gaussian and Impulsive Noise

2017 ◽  
Vol 11 (2) ◽  
pp. 190-202
Author(s):  
Vorapoj Patanavijit ◽  
Kornkamol Thakulsukanant
Keyword(s):  
Gaussian Noise ◽  
Impulsive Noise ◽  
Median Filter ◽  
Power Level ◽  
Empirical Evaluation ◽  
Poor Performance ◽  
Bilateral Filter ◽  
Noise Removal ◽  
Superior Performance ◽  
Trilateral Filter

Since 1998, the Bilateral filter (BF) is worldwide accepted for its performance in practical point of view under Gaussian noise however the Bilateral filter has a poor performance for impulsive noise. Based on the combining of the Rank-Ordered Absolute Differences (ROAD) detection technique and the Bilateral filter for automatically reducing or persecuting of impulsive and Gaussian noise, this Trilateral filter (TF) has been proposed by Roman Garnett et al. since 2005 but the Trilateral filter efficiency is rest absolutely on spatial, radiometric, ROAD and joint impulsivity variance. Hence, this paper computationally determines the optimized values of the spatial, radiometric, ROAD and joint impulsivity variance of the Trilateral filter (TF) for maximum performance. In the experiment, nine noisy standard images (Girl-Tiffany, Pepper, Baboon, House, Resolution, Lena, Airplain, Mobile and Pentagon) under both five power-level Gaussian noise setting and five density impulsive noise setting, are used for estimating optimized parameters of Trilateral filter and for demonstrating the its overall performance, which is compared with classical noise removal techniques such as median filter, linear smoothing filter and Bilateral filter (BF). From the noise removal results of empirically experiments with the highest PSNR criterion, the trilateral filter with the optimized parameters has the superior performance because the ROAD variance and joint impulsivity variance can be statistically analyzed and estimated for each experimental case.

scholarly journals Mid Point Weighted Median Filter for Noise Removal and Smoothening of Images

2019 ◽  
Vol 8 (4) ◽  
pp. 8061-8067
Keyword(s):  
Noise Reduction ◽  
Experimental Work ◽  
Basic Concept ◽  
Impulsive Noise ◽  
Median Filter ◽  
Noise Removal ◽  
Median Filters ◽  
Weighted Median ◽  
Weighted Median Filter

In this paper, a Weighted Median Filter (WMF) mainly Mid-Point WMF (MP WMF) is used to smoothen the images or to remove the impulsive noise present in the input images. It is an improvised version of the median filter. This weighted filter uses the basic concept of the median filter with the enhancement in their mask from normalized mask to the weighted mask. In this weighted median filter, the weight-age is giving to the mid-point pixel i.e. centre pixels or its neighbouring pixels by increasing the repetition of those pixels so that the weight of those mid-point pixel and neighbour pixels get increased. It is shown that the weighted median filter performs more accurately than the normal median filter. Some relationship between MP WMF and other two Four Neighbouring (N4) and Diagonal Neighbouring (ND) Weighted Median Filter are derived. Experimental work has demonstrated that the MP WMF outperform very well than the standard median filters in terms of their noise reduction and in smoothening the image. The proposed MP WMF also provides very good robustness for impulsive noise.

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