An efficient method for the removal of impulse noise from speech and audio signals

2002 ◽  
Author(s):  
C. Chandra ◽  
M.S. Moore ◽  
S.K. Mitra
Keyword(s):  
Efficient Method ◽  
Impulse Noise ◽  
Audio Signals

scholarly journals Reduction of Impulsive Noise from Speech and Audio Signals by using Sd-Rom Algorithm

2021 ◽  
Vol 10 (1) ◽  
pp. 265-268
Author(s):  
G.Manmadha Rao* ◽  
Raidu Babu D.N ◽  
Krishna Kanth P.S.L ◽  
Vinay B. ◽  
Nikhil V.
Keyword(s):  
Impulse Noise ◽  
Impulsive Noise ◽  
Rank Order ◽  
Signal To Noise Ratio ◽  
Audio Signal ◽  
Window Size ◽  
Mean Value ◽  
Audio Signals ◽  
Signal To Noise ◽  
Noise Ratio

Removal of noise is the heart for speech and audio signal processing. Impulse noise is one of the most important noise which corrupts different parts in speech and audio signals. To remove this type of noise from speech and audio signals the technique proposed in this work is signal dependent rank order mean (SD-ROM) method in recursive version. This technique is used to replace the impulse noise samples based on the neighbouring samples. It detects the impulse noise samples based on the rank ordered differences with threshold values. This technique doesn’t change the features and tonal quality of signal. Rank ordered differences is used for detecting the impulse noise samples in speech and audio signals. Once the sample is detected as corrupted sample, that sample is replaced with rank ordered mean value and this rank ordered mean value depends on the sliding window size and neighbouring samples. This technique shows good results in terms of signal to noise ratio (SNR) and peak signal to noise ratio (PSNR) when compared with other techniques. It mainly used for removal of impulse noises from speech and audio signals.

Outreach Opportunities Using the Instructional SEM at Iowa State University

1996 ◽  
Vol 54 ◽  
pp. 412-413
Author(s):  
L. S. Chumbley ◽  
M. Meyer ◽  
K. Fredrickson ◽  
F.C. Laabs
Keyword(s):  
Materials Science ◽  
State University ◽  
Digital Cameras ◽  
Audio Signals ◽  
Iowa State University ◽  
Cornell University ◽  
Sem Image ◽  
Local Schools ◽  
Materials Science And Engineering ◽  
Video And Audio

The development of a scanning electron microscope (SEM) suitable for instructional purposes has created a large number of outreach opportunities for the Materials Science and Engineering (MSE) Department at Iowa State University. Several collaborative efforts are presently underway with local schools and the Department of Curriculum and Instruction (C&I) at ISU to bring SEM technology into the classroom in a near live-time, interactive manner. The SEM laboratory is shown in Figure 1.Interactions between the laboratory and the classroom use inexpensive digital cameras and shareware called CU-SeeMe, Figure 2. Developed by Cornell University and available over the internet, CUSeeMe provides inexpensive video conferencing capabilities. The software allows video and audio signals from Quikcam™ cameras to be sent and received between computers. A reflector site has been established in the MSE department that allows eight different computers to be interconnected simultaneously. This arrangement allows us to demonstrate SEM principles in the classroom. An Apple Macintosh has been configured to allow the SEM image to be seen using CU-SeeMe.

An Effective FPGA Implementation of Denoising of Impulse Noise in Images

2016 ◽  
Vol 1 (3) ◽  
pp. 19-25
Author(s):  
Jeniffer A ◽  
Haripasath S ◽  
Chinthamani S ◽  
Chitra G ◽  
Karthiga V
Keyword(s):  
Impulse Noise ◽  
Fpga Implementation
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