scholarly journals An adaptive Sliding Window based on Fuzzy Filter for removing Wide-range Impulse Noise Densities on the Image Sequence

2013 ◽  
Author(s):  
Fitri Utaminingrum ◽  
Keiichi Uchimura ◽  
Gou Koutaki
Keyword(s):  
Impulse Noise ◽  
Sliding Window ◽  
Image Sequence ◽  
Fuzzy Filter ◽  
Wide Range

Directional weighted hybrid median based fuzzy filter for de-noising random valued impulse noise

2020 ◽  
Author(s):  
R. Marudhachalam ◽  
S. Selvanayaki ◽  
R. Tamilselvi ◽  
P. Devaki
Keyword(s):  
Impulse Noise ◽  
Fuzzy Filter

A fuzzy filter for the removal of random impulse noise in image sequences

2011 ◽  
Vol 29 (6) ◽  
pp. 407-419 ◽  
Author(s):  
Tom Mélange ◽  
Mike Nachtegael ◽  
Stefan Schulte ◽  
Etienne E. Kerre
Keyword(s):  
Impulse Noise ◽  
Image Sequences ◽  
Fuzzy Filter ◽  
Random Impulse

A Review of Gunshot Noise as Factor in Hearing Disorders

2019 ◽  
Vol 105 (6) ◽  
pp. 904-911 ◽  
Author(s):  
Ewa Skrodzka ◽  
Andrzej Wicher ◽  
Roman Gołe¸biewski
Keyword(s):  
Hearing Loss ◽  
Hair Cells ◽  
Impulse Noise ◽  
Noise Exposure ◽  
Single Shot ◽  
Negative Consequences ◽  
Mean Values ◽  
Sport Training ◽  
Wide Range ◽  
Auditory Systems

The impulse noise produced by personal weapons (guns, rifles, shotguns) during military activity, and while people engage in sport, training and hunting, is a threat to the auditory systems of soldiers, civilians, policemen, hunters, forest officers, sportspeople and bystanders not actively engaged in professional or recreational firing. An overview of noise levels generated by different types of weapon is provided, and potential short-term and long-term consequences for the human auditory system are described. The mean values of LC, peak sound pressure level during the shot, at the shooter's ears, for various types of weapons are approximately 160 dB SPL. These are levels that can cause permanent, irreversible negative effects on hearing (hearing loss, tinnitus, etc.) even as a result of a single shot being fired. One of the largest groups of weapon users in Poland (about 120 thousand) are hunters and field masters. They are not obligated by any regulations to protect their auditory systems from impulse noise. This means that this group of firearm users is at particularly high risk of hearing damage. On the basis of the literature review, it is shown that hearing exposure to high-level impulse noise such as a gunshot can result in such consequences as damage to the middle ear and destruction of the outer/inner hair cells in the cochlea. Especially difficult to diagnose is 'hidden hearing loss', i.e. damage to the synaptic connections between the hair cells of the inner ear and the auditory nerve fibres, which is not reflected in the results of basic audiometric testing and can cause hearing problems many years after impulse noise exposure. The wide range of negative consequences of gunfire noise clearly indicates the need for the hearing of the shooters to be protected.

scholarly journals Sliding Window Temporal Graph Coloring

2019 ◽  
Vol 33 ◽  
pp. 7667-7674 ◽  
Author(s):  
George B. Mertzios ◽  
Hendrik Molter ◽  
Viktor Zamaraev
Keyword(s):  
Graph Coloring ◽  
Time Window ◽  
Linear Time ◽  
Sliding Window ◽  
Planning And Scheduling ◽  
Coloring Problem ◽  
Wide Range ◽  
Temporal Graph ◽  
Changes Over Time ◽  
Over Time

Graph coloring is one of the most famous computational problems with applications in a wide range of areas such as planning and scheduling, resource allocation, and pattern matching. So far coloring problems are mostly studied on static graphs, which often stand in stark contrast to practice where data is inherently dynamic and subject to discrete changes over time. A temporal graph is a graph whose edges are assigned a set of integer time labels, indicating at which discrete time steps the edge is active. In this paper we present a natural temporal extension of the classical graph coloring problem. Given a temporal graph and a natural number ∆, we ask for a coloring sequence for each vertex such that (i) in every sliding time window of ∆ consecutive time steps, in which an edge is active, this edge is properly colored (i.e. its endpoints are assigned two different colors) at least once during that time window, and (ii) the total number of different colors is minimized. This sliding window temporal coloring problem abstractly captures many realistic graph coloring scenarios in which the underlying network changes over time, such as dynamically assigning communication channels to moving agents. We present a thorough investigation of the computational complexity of this temporal coloring problem. More specifically, we prove strong computational hardness results, complemented by efficient exact and approximation algorithms. Some of our algorithms are linear-time fixed-parameter tractable with respect to appropriate parameters, while others are asymptotically almost optimal under the Exponential Time Hypothesis (ETH).

Removal of random valued impulse noise from grayscale images using quadrant based spatially adaptive fuzzy filter

2020 ◽  
Vol 169 ◽  
pp. 107403 ◽  
Author(s):  
M. Nadeem ◽  
Ayyaz Hussain ◽  
Asim Munir ◽  
M. Habib ◽  
M. Tahir Naseem
Keyword(s):  
Impulse Noise ◽  
Fuzzy Filter ◽  
Adaptive Fuzzy ◽  
Spatially Adaptive ◽  
Grayscale Images

Impulse noise removal by k-means clustering identified fuzzy filter: a new approach

2020 ◽  
Vol 28 (5) ◽  
pp. 2838-2862
Author(s):  
Aritra BANDYOPADHYAY ◽  
Kaustuv DEB ◽  
Atanu DAS ◽  
Rajib BAG
Keyword(s):  
Impulse Noise ◽  
Noise Removal ◽  
Fuzzy Filter ◽  
New Approach ◽  
Impulse Noise Removal

Impulse noise removal using SVM classification based fuzzy filter from gray scale images

2016 ◽  
Vol 128 ◽  
pp. 262-273 ◽  
Author(s):  
Amarjit Roy ◽  
Joyeeta Singha ◽  
Salam Shuleenda Devi ◽  
Rabul Hussain Laskar
Keyword(s):  
Impulse Noise ◽  
Noise Removal ◽  
Fuzzy Filter ◽  
Gray Scale ◽  
Svm Classification ◽  
Impulse Noise Removal

scholarly journals Execution of Median Filter Built on FPGA for Trimming Noise Meeting the Real Time Requirements

2019 ◽  
Vol 8 (4) ◽  
pp. 7855-7858
Keyword(s):  
Real Time ◽  
Impulse Noise ◽  
Noise Suppression ◽  
Median Filter ◽  
Sliding Window ◽  
Spatial Filter ◽  
Effective Technique ◽  
The Real ◽  
Time Requirements ◽  
Suppression Process

As images plays a vital in all aspects, there is a need to met the real time requirements in processing the image. Major challenges raised in processing the image is noise. The utmost typical difficult is effective denoising creation as well as quick functioning in the processing of digital image noise suppression process for the need of real time consequences to afford image with high quality this project was introduced. Generally filters plays a major role to remove the impulse noise in acquired images. The filter named sliding window spatial filter which is familiar as median filter is effective technique to eradicate impulse noise from the devoleped image. But in real time, it is very difficult to execute. To overcome this, FPGA methodology is introduced to fulfills the support besides the optimization of major constraints like area, speed, power. In addition to this, it assures technical sustenance of eradicating noise in image as per requirements in real time. Regarding the design and structure appearances in FPGA, Xilinx software is used for simulation and code has been written in Verilog language.

Sign in / Sign up

Export Citation Format

Share Document