Design of Exponentially Weighted Median Filter Cascaded With Adaptive Median Filter

Abstract The objective of this paper is to design an II phase algorithm employing median filters for enlightening the performance in removing impulse noise during the processing of the image. The cascaded filter section employs an Adaptive median filter in the first phase followed by a Recursive weighted median filter (RWM) in the second phase. The RWM filter weight is selected with the Median Controlled Algorithm. As a design parameter, the exponential weights of RWM filters are used in the feedback path. The projected algorithm can achieve suggestively improved quality of image when compared to fixed weight or the Center Weighted Median filters.

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Wavelet-Based Weighted Median Filter For Image Denoising Of MRI Brain Images

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v10.i1.pp201-206 ◽

2018 ◽

Vol 10 (1) ◽

pp. 201 ◽

Cited By ~ 1

Author(s):

N. Rajalakshmi ◽

K. Narayanan ◽

P. Amudhavalli

Keyword(s):

Additive White Gaussian Noise ◽

Median Filter ◽

Wiener Filter ◽

Brain Images ◽

Visual Appearance ◽

Mri Brain ◽

Weighted Median ◽

Weighted Median Filter ◽

Mri Brain Images

<p>Preliminary diagnosing of MRI images from the hospital cannot be relied on because of the chances of occurrence of artifacts resulting in degraded quality of image, while others may be confused with pathology. Obtained MRI image usually contains limited artifacts. It becomes complex one for doctors in analyzing them. By increasing the contrast of an image, it will be easy to analyze. In order to find the tumor part efficiently MRI brain image should be enhanced properly. The image enhancement methods mainly improve the visual appearance of MRI images. The goal of denoising is to remove the noise, which may corrupt an image during its acquisition or transmission, while retaining its quality. In this paper effectiveness of seven denoising algorithms viz. median filter, wiener filter, wavelet filter, wavelet based wiener, NLM, wavelet based NLM, proposed wavelet based weighted median filter(WMF) using MRI images in the presence of additive white Gaussian noise is compared. The experimental results are analyzed in terms of various image quality metrics.</p>

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Modified Filter Equation with Improved Fuzzy Logic System Based Directional Median Filter for Mixed Noise

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.g8946.0510721 ◽

2021 ◽

Vol 10 (7) ◽

pp. 83-90

Author(s):

Bhageerath Singh Kaurav* ◽

Karuna Markam ◽

Pooja Sahoo

Keyword(s):

Fuzzy Logic ◽

Signal To Noise Ratio ◽

Median Filter ◽

Fuzzy Logic System ◽

Median Filters ◽

Switching Median Filter ◽

Weighted Median ◽

Mixed Noise ◽

Weighted Median Filter ◽

Logic System

DWM (Directional weighted median) filter is very popular in filtering digital image and remove mixed noise. Fuzzy logic is implemented with median filters to improve its performance. In the previous work, fuzzy logic system is implemented with switching median filter and gives better performance than directional median filter as well as switching median filter. Experimenting directional median filter with same fuzzy logic system didn’t yield to better results therefore fuzzy logic parameters has been changes as per strong points of directional weighted median filter and a constant has been included in the filtering equation to improve the results. So in this proposed work, we have successfully implemented directional weighted median filter with fuzzy logic system which is proving better results than DWM and FSMF (Fuzzy Switching Median Filter). PSNR (Peak Signal to Noise Ratio)is used for qualitative analysis of results.

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MEDIAN BASED IDEMPOTENT FILTERS

Journal of Circuits System and Computers ◽

10.1142/s0218126691000021 ◽

1991 ◽

Vol 01 (02) ◽

pp. 125-148 ◽

Cited By ~ 22

Author(s):

P. HAAVISTO ◽

M. GABBOUJ ◽

Y. NEUVO

Keyword(s):

Speech Processing ◽

Impulsive Noise ◽

Median Filter ◽

Sufficient Conditions ◽

3 Dimensional ◽

Median Filters ◽

Filter Output ◽

Class 1 ◽

Weighted Median ◽

Weighted Median Filters

Idempotent filters produce a root signal in a single filter pass, i.e. the filter output is invariant to further filterings with the same filter. In this paper median based idempotent filter structures are introduced. Two approaches to generate these filters are studied: weighted median filters and median filter cascades. Two subclasses of n-dimensional idempotent weighted median filters, called Class 1 and Class 2 filters in the paper, are introduced. It is shown that both Class 1 and Class 2 filters suppress impulsive noise from n-dimensional input signals and yet have almost no effect on the non-corrupted parts of the signal. These filters are therefore well-suited for example for preprocessing purposes. An application to speech processing is described. Other likely applications of these filters are in image processing and, also, in image sequence processing, where the filter mask is typically 3-dimensional. Sufficient conditions for a filter cascade to be idempotent are given. Two idempotent median filter cascades and their advantages are discussed.

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Design of Decision Based Recursive Weighted Median Filter With Exponential Weights

Journal of Physics Conference Series ◽

10.1088/1742-6596/2089/1/012016 ◽

2021 ◽

Vol 2089 (1) ◽

pp. 012016

Author(s):

Motepalli Siva Rama Ganesh ◽

Kalyan Sagar Kadali ◽

Ramu Bhukya ◽

Y.T.R. Palleswari ◽

Asapu Siva ◽

...

Keyword(s):

Impulse Noise ◽

Median Filter ◽

Mean Square ◽

Noise Levels ◽

Exponential Weights ◽

High Noise ◽

Median Filters ◽

Weighted Median ◽

Weighted Median Filter ◽

Image Details

Abstract The prescribed algorithm for removing impulse noise effectively even under high noise densities without causing any loss of image details. Hence a cascaded section of median filters that, involves an Decision-based Median Filter followed by a Recursive Weighted Median (RWM) Filter employing exponential weights are used. The median controlled algorithm is employed to calculate the exponential weights. In the algorithms that where proposed in earlier which involves a cascaded section of the median with the RWM filters provided lesser Peak Signal/Noise Ratio (PSNR) and greater Mean Square Error(MSE) values. Hence the output appeared to be distorted for higher noise levels. These drawbacks have been eliminated in this proposed algorithm.

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

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.d8175.118419 ◽

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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