scholarly journals Improved deconvolution of very weak confocal signals

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 787 ◽  
Author(s):  
Kasey J. Day ◽  
Patrick J. La Rivière ◽  
Talon Chandler ◽  
Vytas P. Bindokas ◽  
Nicola J. Ferrier ◽  
...  
Keyword(s):  
Background Noise ◽  
Signal To Noise Ratio ◽  
Simulated Data ◽  
Time Lapse ◽  
Confocal Image ◽  
Signal To Noise ◽  
4D Imaging ◽  
Fluorescence Images ◽  
Gaussian Blur ◽  
Imaging Conditions

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal of background noise. This approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage.

scholarly journals Improved deconvolution of very weak confocal signals

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 787 ◽  
Author(s):  
Kasey J. Day ◽  
Patrick J. La Rivière ◽  
Talon Chandler ◽  
Vytas P. Bindokas ◽  
Nicola J. Ferrier ◽  
...  
Keyword(s):  
Background Noise ◽  
Signal To Noise Ratio ◽  
Simulated Data ◽  
Time Lapse ◽  
Confocal Image ◽  
Signal To Noise ◽  
4D Imaging ◽  
Fluorescence Images ◽  
Gaussian Blur ◽  
Imaging Conditions

Deconvolution is typically used to sharpen fluorescence images, but when the signal-to-noise ratio is low, the primary benefit is reduced noise and a smoother appearance of the fluorescent structures. 3D time-lapse (4D) confocal image sets can be improved by deconvolution. However, when the confocal signals are very weak, the popular Huygens deconvolution software erases fluorescent structures that are clearly visible in the raw data. We find that this problem can be avoided by prefiltering the optical sections with a Gaussian blur. Analysis of real and simulated data indicates that the Gaussian blur prefilter preserves meaningful signals while enabling removal of background noise. This approach is very simple, and it allows Huygens to be used with 4D imaging conditions that minimize photodamage.

Selecting the Optimal FM System for Children With Cochlear Implants

2008 ◽  
Vol 18 (1) ◽  
pp. 19-24
Author(s):  
Erin C. Schafer
Keyword(s):  
Speech Recognition ◽  
Cochlear Implants ◽  
Empirical Research ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Evidence Based ◽  
Signal To Noise ◽  
Speech Processor ◽  
System Input ◽  
Optimal Type

Children who use cochlear implants experience significant difficulty hearing speech in the presence of background noise, such as in the classroom. To address these difficulties, audiologists often recommend frequency-modulated (FM) systems for children with cochlear implants. The purpose of this article is to examine current empirical research in the area of FM systems and cochlear implants. Discussion topics will include selecting the optimal type of FM receiver, benefits of binaural FM-system input, importance of DAI receiver-gain settings, and effects of speech-processor programming on speech recognition. FM systems significantly improve the signal-to-noise ratio at the child's ear through the use of three types of FM receivers: mounted speakers, desktop speakers, or direct-audio input (DAI). This discussion will aid audiologists in making evidence-based recommendations for children using cochlear implants and FM systems.

Multilag Correlation Estimators for Polarimetric Radar Measurements in the Presence of Noise

2012 ◽  
Vol 29 (6) ◽  
pp. 772-795 ◽  
Author(s):  
Lei Lei ◽  
Guifu Zhang ◽  
Richard J. Doviak ◽  
Robert Palmer ◽  
Boon Leng Cheong ◽  
...  
Keyword(s):  
Theoretical Analysis ◽  
Data Quality ◽  
Signal To Noise Ratio ◽  
Simulated Data ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Signal To Noise ◽  
Spectral Moments ◽  
Radar Measurements

Abstract The quality of polarimetric radar data degrades as the signal-to-noise ratio (SNR) decreases. This substantially limits the usage of collected polarimetric radar data to high SNR regions. To improve data quality at low SNRs, multilag correlation estimators are introduced. The performance of the multilag estimators for spectral moments and polarimetric parameters is examined through a theoretical analysis and by the use of simulated data. The biases and standard deviations of the estimates are calculated and compared with those estimates obtained using the conventional method.

Speech in noise testing before and after grommet insertion

2012 ◽  
Vol 126 (10) ◽  
pp. 1010-1015 ◽  
Author(s):  
V Possamai ◽  
G Kirk ◽  
A Scott ◽  
D Skinner
Keyword(s):  
Small Group ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Sound Field ◽  
Noise Signal ◽  
Signal To Noise ◽  
Speech In Noise ◽  
Before And After ◽  
Noise Test ◽  
Noise Ratio

AbstractObjectives:To assess the feasibility of designing and implementing a speech in noise test in children before and after grommet insertion, and to analyse the results of such a test in a small group of children.Methods:Twelve children aged six to nine years who were scheduled to undergo grommet insertion were identified. They underwent speech in noise testing before and after grommet insertion. This testing used Arthur Boothroyd word lists read at 60 dB in four listening conditions presented in a sound field: firstly in quiet conditions, then in signal to noise ratios of +10 (50 dB background noise), 0 (60 dB) and −10 (70 dB).Results:Mean phoneme scores were: in quiet conditions, 28.1 pre- and 30 post-operatively (p = 0.04); in 50 dB background noise (signal to noise ratio +10), 24.2 pre- and 29 post-operatively (p < 0.01); in 60 dB background noise (signal to noise ratio 0), 22.6 pre- and 27.5 post-operatively (p = 0.06); and in 70 dB background noise (signal to noise ratio −10), 13.9 pre- and 21 post-operatively (p = 0.05).Conclusion:This small study suggests that speech in noise testing is feasible in this scenario. Our small group of children demonstrated a significant improvement in speech in noise scores following grommet insertion. This is likely to translate into a significant advantage in the educational environment.

scholarly journals Super-Resolution Reconstruction of Cell Pseudo-Color Image Based on Raman Technology

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4076
Author(s):  
Yang ◽  
Zhu ◽  
Wang ◽  
Yang ◽  
Wu ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Raman Spectrum ◽  
Background Noise ◽  
Color Image ◽  
Signal To Noise Ratio ◽  
Super Resolution ◽  
Reconstruction Algorithm ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Pseudo Color

Raman spectroscopy visualization is a challenging task due to the interference of complex background noise and the number of selected measurement points. In this paper, a super-resolution image reconstruction algorithm for Raman spectroscopy is studied to convert raw Raman data into pseudo-color super-resolution imaging. Firstly, the Raman spectrum data of a single measurement point is measured multiple times to calculate the mean value to remove the random background noise, and innovatively introduce the Retinex algorithm and the median filtering algorithm which improve the signal-to-noise ratio. The novel method of using deep neural network performs a super-resolution reconstruction operation on the gray image. An adaptive guided filter that automatically adjusts the filter radius and penalty factor is proposed to highlight the contour of the cell, and the super-resolution reconstruction of the pseudo-color image of the Raman spectrum is realized. The average signal-to-noise ratio of the reconstructed pseudo-color image sub-band reaches 14.29 db, and the average value of information entropy reaches 4.30 db. The results show that the Raman-based cell pseudo-color image super-resolution reconstruction algorithm is an effective tool to effectively remove noise and high-resolution visualization. The contrast experiments show that the pseudo-color image Kullback–Leiber (KL) entropy of the color image obtained by the method is small, the boundary is obvious, and the noise is small, which provide technical support for the development of sophisticated single-cell imaging Raman spectroscopy instruments.

Uncertainty and Signal-to-Noise Ratio for Unsteady Background Noise

2018 ◽  
Vol 66 (2) ◽  
pp. 131-141 ◽  
Author(s):  
Wongyu Choi ◽  
Michael B. Pate ◽  
James F. Sweeney
Keyword(s):  
Background Noise ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals The Effect of Background Noise on Intelligibility of Dysphonic Speech

2017 ◽  
Vol 60 (7) ◽  
pp. 1919-1929 ◽  
Author(s):  
Keiko Ishikawa ◽  
Suzanne Boyce ◽  
Lisa Kelchner ◽  
Maria Golla Powell ◽  
Heidi Schieve ◽  
...  
Keyword(s):  
Speech Perception ◽  
Strong Correlation ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Cepstral Peak Prominence ◽  
Intelligibility Score ◽  
Future Work ◽  
The Relationship ◽  
Acoustic Measure

Purpose The aim of this study is to determine the effect of background noise on the intelligibility of dysphonic speech and to examine the relationship between intelligibility in noise and an acoustic measure of dysphonia: cepstral peak prominence (CPP). Method A study of speech perception was conducted using speech samples from 6 adult speakers with typical voice and 6 adult speakers with dysphonia. Speech samples were presented to 30 listeners with typical hearing in 3 noise conditions: quiet, signal-to-noise ratio (SNR)+5, and SNR+0. Intelligibility scores were obtained via orthographic transcription as the percentage of correctly identified words. Speech samples were acoustically analyzed using CPP, and the correlation between the CPP measurements and intelligibility scores was examined. Results The intelligibility of both typical and dysphonic speech was reduced as the level of background noise increased. The reduction was significantly greater in dysphonic speech. A strong correlation was noted between CPP and intelligibility score at SNR+0. Conclusions Dysphonic speech is relatively harder to understand in the presence of background noise as compared with typical speech. CPP may be a useful predictor of this intelligibility deficit. Future work is needed to confirm these findings with a larger number of speakers and speech materials with known predictability.

Effect of Drillstring Vibrations on MWD Pressure Pulse Signals

1990 ◽  
Vol 112 (2) ◽  
pp. 84-89 ◽  
Author(s):  
W. E. Lear ◽  
D. W. Dareing
Keyword(s):  
Background Noise ◽  
Pressure Pulse ◽  
Signal To Noise Ratio ◽  
Drilling Fluid ◽  
Operating Conditions ◽  
Closing Time ◽  
Signal To Noise ◽  
Measurement While Drilling ◽  
Valve Opening ◽  
Axial Vibrations

Axial vibrations of drillstrings produce pressure variations within the drilling fluid column. These pressure variations are imposed on controlled pressure pulse signals from Measurement-While-Drilling (MWD) tools producing background noise in pressure pulse data measured at the rig. The paper shows the effect on signal-to-noise ratio for various operating conditions, such as vibration frequency, valve opening/closing time, pulsing interval, and flow rate.

Effects of Speech Rate, Background Noise, and Simulated Hearing Loss on Speech Rate Judgment and Speech Intelligibility in Young Listeners

2009 ◽  
Vol 20 (01) ◽  
pp. 028-039 ◽  
Author(s):  
Elizabeth M. Adams ◽  
Robert E. Moore
Keyword(s):  
Hearing Loss ◽  
Research Design ◽  
Background Noise ◽  
Speech Intelligibility ◽  
Signal To Noise Ratio ◽  
Speech Rate ◽  
Normal Hearing ◽  
Moderate Correlation ◽  
Signal To Noise ◽  
Noise Ratio

Purpose: To study the effect of noise on speech rate judgment and signal-to-noise ratio threshold (SNR50) at different speech rates (slow, preferred, and fast). Research Design: Speech rate judgment and SNR50 tasks were completed in a normal-hearing condition and a simulated hearing-loss condition. Study Sample: Twenty-four female and six male young, normal-hearing participants. Results: Speech rate judgment was not affected by background noise regardless of hearing condition. Results of the SNR50 task indicated that, as speech rate increased, performance decreased for both hearing conditions. There was a moderate correlation between speech rate judgment and SNR50 with the various speech rates, such that as judgment of speech rate increased from too slow to too fast, performance deteriorated. Conclusions: These findings can be used to support the need for counseling patients and their families about the potential advantages to using average speech rates or rates that are slightly slowed while conversing in the presence of background noise.

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