Design of a multichannel two-dimensional delta-domain lattice filter for noise removal

2001 ◽  
Vol 49 (7) ◽  
pp. 1581-1593 ◽  
Author(s):  
C.M. Hendekli ◽  
A. Ertuzun
Keyword(s):  
Noise Removal ◽  
Two Dimensional ◽  
Lattice Filter ◽  
Domain Lattice

Intuitionistic Fuzzy Filters for Noise Removal in Images

2016 ◽  
pp. 53-64
Author(s):  
C. Radhika ◽  
R. Parvathi ◽  
N. Karthikeyani Visalakshi
Keyword(s):  
Image Processing ◽  
Information Processing ◽  
Comparative Analysis ◽  
Noise Removal ◽  
Two Dimensional ◽  
Intuitionistic Fuzzy ◽  
Input And Output ◽  
Fuzzy Filters ◽  
Standard Techniques ◽  
Filtering Techniques

Image processing is any form of information processing in which both input and output are images. Most of the image processing involves in treating the image as two dimensional representations and applying standard techniques to it. Images contain lot of uncertainties and are fuzzy/vague in nature. Various fuzzy filtering techniques are defined for noise removal in image processing and these existing filters helps to enhance the image using only the membership values. Further, by incorporating intuitionistic fuzzy filters, vagueness and ambiguity are managed by taking the non-membership values also into consideration. In this paper, light is thrown on some important types of noise and a comparative analysis is done. This paper also presents the results of applying different noise types to an image and investigates the results of various intuitionistic fuzzy filtering techniques. A comparison is made on the results of all the techniques.

scholarly journals Tracking and Linking of Microparticle Trajectories During Mode-Coupling Induced Melting in a Two-Dimensional Complex Plasma Crystal

2019 ◽  
Vol 5 (3) ◽  
pp. 41
Author(s):  
Lénaïc Couëdel ◽  
Vladimir Nosenko
Keyword(s):  
Mode Coupling ◽  
Signal To Noise Ratio ◽  
Scattered Light ◽  
Three Dimensional ◽  
Light Sheet ◽  
Noise Removal ◽  
Two Dimensional ◽  
Complex Plasma ◽  
Plasma Crystal ◽  
Mode Coupling Instability

In this article, a strategy to track microparticles and link their trajectories adapted to the study of the melting of a quasi two-dimensional complex plasma crystal induced by the mode-coupling instability is presented. Because of the three-dimensional nature of the microparticle motions and the inhomogeneities of the illuminating laser light sheet, the scattered light intensity can change significantly between two frames, making the detection of the microparticles and the linking of their trajectories quite challenging. Thanks to a two-pass noise removal process based on Gaussian blurring of the original frames using two different kernel widths, the signal-to-noise ratio was increased to a level that allowed a better intensity thresholding of different regions of the images and, therefore, the tracking of the poorly illuminated microparticles. Then, by predicting the positions of the microparticles based on their previous positions, long particle trajectories could be reconstructed, allowing accurate measurement of the evolution of the microparticle energies and the evolution of the monolayer properties.

scholarly journals A Modified Trimmed Median Filter Technique for Noise Removal in an Image

2019 ◽  
Vol 8 (6S4) ◽  
pp. 583-586
Keyword(s):  
Median Filter ◽  
Noise Removal ◽  
Two Dimensional ◽  
Noisy Pixel ◽  
Quality Testing ◽  
Filtering Technique ◽  
Pixel Value ◽  
Simulation Results ◽  
Salt And Pepper ◽  
Filtration Technique

A modified trimmed filtration that is actually median when it comes to recovering the original images that are dishonored by the salt & pepper noise is actually presented here.The refined the pixels tend to be checked for high or least pixel values for example, 0 or 255 in this suggested method. Then this expedient pixel is recognized as the noisy one otherwise maybe not a noisy one in the event that processed pixel is actually 0 or 255. A two-dimensional 3*3 window can end up being selected with this specific noisy pixel as center component and being a running pixel. In this 3*3 window, then this algorithm can replace the value of the loud pixel as mean of these 9 elements in the 3*3 screen if all 9 aspects in the window are values like 0’s or 255’s. Then this modified trimmed median filtration technique can be applied if most of the 9 elements tend to be not 0’s or 255’s. This formula can eliminate the 0’s and present that is 255’s the 3*3 window and change the loud pixel value as average of mean and median of this remaining pixel in 3*3 screen. Simulation results imply that the proposed modified trimmed filter that is actually median can be works really in the event that picture can end up being influenced by salt and pepper sound.The outcome obtained from the recommended modified trimmed filter is compared with the AWMF, DBUTVF, and MDBUTMF. This proposed MTMF filtering technique is actually analyzed on various images for different quality testing parameters like PSNR, MSE.

Noise removal using a nonlinear two-dimensional diffusion network

1998 ◽  
Vol 53 (11-12) ◽  
pp. 483-487
Author(s):  
Jean-Christophe Comte ◽  
Patrick Marquié ◽  
Jean-Marie Bilbault ◽  
Stéphane Binczak
Keyword(s):  
Noise Removal ◽  
Two Dimensional ◽  
Dimensional Diffusion

Intuitionistic Fuzzy Filters for Noise Removal in Images

Biometrics ◽  
2017 ◽  
pp. 1643-1655
Author(s):  
C. Radhika ◽  
R. Parvathi ◽  
N. Karthikeyani Visalakshi
Keyword(s):  
Image Processing ◽  
Information Processing ◽  
Comparative Analysis ◽  
Noise Removal ◽  
Two Dimensional ◽  
Intuitionistic Fuzzy ◽  
Input And Output ◽  
Fuzzy Filters ◽  
Standard Techniques ◽  
Filtering Techniques

Image processing is any form of information processing in which both input and output are images. Most of the image processing involves in treating the image as two dimensional representations and applying standard techniques to it. Images contain lot of uncertainties and are fuzzy/vague in nature. Various fuzzy filtering techniques are defined for noise removal in image processing and these existing filters helps to enhance the image using only the membership values. Further, by incorporating intuitionistic fuzzy filters, vagueness and ambiguity are managed by taking the non-membership values also into consideration. In this paper, light is thrown on some important types of noise and a comparative analysis is done. This paper also presents the results of applying different noise types to an image and investigates the results of various intuitionistic fuzzy filtering techniques. A comparison is made on the results of all the techniques.

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