Under Water Noise Reduction Using Wavelet and Savitzky-Golay

Balan, Selva; Khaparde, Arti; Tank, Vanita Raj; Rade, Tejashri; Takalkar, Kirti

doi:10.5121/csit.2014.4421

Cited by 7 publications

(5 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…And also of mangroves present in that Wetland, Which is inside that boundary. The multipath noise is removed by applying stationary wavelet decomposition in the data set [3].…”

Section: B Preprocessingmentioning

confidence: 99%

Performance Evaluation of Bathymetry Data using Statistical Techniques to Remove Underwater Noise

Selva¹,

Anjali²,

Shini³

2018

IJCA

View full text Add to dashboard Cite

Analysis of bathymetry information is a testing errand because of a few reasons. The information is gathered remotely which is huge in size. Bathymetry information contains the profundity estimations of water body at different areas. The data obtained is also affected by noise and needs to be processed to predict the bottom of reservoir and water body. This data is prepared to produce a 3D plot by introducing the transitional estimations of the plot. The bathymetry information comprises of different commotions which are evacuated by applying noise expulsion calculations lastly the volume of water is anticipated. This paper presents different noise evacuation systems on bathymetry information to anticipate the volume of water in a supply.

show abstract

“…And also of mangroves present in that Wetland, Which is inside that boundary. The multipath noise is removed by applying stationary wavelet decomposition in the data set [3].…”

Section: B Preprocessingmentioning

confidence: 99%

Performance Evaluation of Bathymetry Data using Statistical Techniques to Remove Underwater Noise

Selva¹,

Anjali²,

Shini³

2018

IJCA

View full text Add to dashboard Cite

show abstract

“…The ultrasonic signal is commonly used for depth estimation [5]. This signal is affected by underwater noises which result in inaccurate depth measurements.…”

Section: Signal Decompositionmentioning

confidence: 99%

A Literature Survey on Ambient Noise Analysis For underwater Acoustic Signals

Yashaswini¹,

Halagur²,

Khan³

et al. 2015

IJCES

View full text Add to dashboard Cite

Transmitting data with water as the medium is called underwater communication. Electromagnetic signals are better attenuated in water than sound. Hence it is the most reliable and versatile means of communication underwater. The acoustic signals will be affected by ocean driven noise during transmission. Ambient noise is the background noise which has to be subtracted from the acoustic signal for smooth transmission. Hence the recognition and reduction of ambient noise is the essential part of underwater signal transmission. Studies and research are being carried out extensively in this area. There are many works reported and the research is still in progress. This literature survey presents the work done on the research front of ambient noise affecting acoustic signals.

show abstract

“…Many researchers have conducted useful investigations in recent years, primarily focusing on wavelet denoising, Fast Fourier Transform (FFT), and multiscale decomposition methods to improve the signal-to-noise ratio of underwater target radiation noise. Zhao et al [1][2][3][4][5][6][7][8] proposed a wavelet relative energy criterion, and the results show that after the node segmentation threshold process, the noise band signal and the target band signal can be effectively separated. This method outperforms the global single denoising method in terms of separation and denoising.…”

Section: Introductionmentioning

confidence: 99%

Compressed Sensing Multiscale Sample Entropy Feature Extraction Method for Underwater Target Radiation Noise

Lei

Lei²,

Zhou

et al. 2022

IEEE Access

View full text Add to dashboard Cite

Accurate underwater target detection and recognition in complex marine environments has always been a challenge. There is a lot of information in underwater target radiation noise that is important for underwater target recognition. However, the traditional underwater target radiation noise process is inefficient and inaccurate, severely limiting underwater target recognition. This paper proposed a new method for underwater target recognition based on compressed sensing multiscale entropy. For starters, compressing a signal improves its signal-to-noise ratio and broadens its linear spectrum. The multiscale sample entropy for the signal is then calculated after it has been denoised, and the most separated sample entropy is chosen by comparing the different scales of sample entropy to achieve effective underwater target radiation noise recognition. The experimental results show that the feature extraction method proposed in the paper can classify underwater target radiation noise quickly and effectively, improving recognition efficiency.

show abstract

Under Water Noise Reduction Using Wavelet and Savitzky-Golay

Abstract: ABSTRACT

Cited by 7 publications

References 6 publications

Performance Evaluation of Bathymetry Data using Statistical Techniques to Remove Underwater Noise

Performance Evaluation of Bathymetry Data using Statistical Techniques to Remove Underwater Noise

A Literature Survey on Ambient Noise Analysis For underwater Acoustic Signals

Compressed Sensing Multiscale Sample Entropy Feature Extraction Method for Underwater Target Radiation Noise

Contact Info

Product

Resources

About