Effective Residual and Regional Gravity Anomaly Separation - Using 1-D & 2-D Stationary Wavelet Transform

Naeim Mousavi, Vahid E. Ardestani, Hassan Moosavi

Abstract

Numerous studies on capabilities of de-noising and separation by wavelet were performed, and their all aims more and less was elimination of possible largest nongeological factors, noise, and to achieve pure regional effects free from residuals. De-noising could be used for removal of non-desired effects like latitude, terrain, tides, drift etc., from our desired portion of data as target. Separations of anomalies that are not of interest conclude shallow structure is suitable to be optimal. Hence detection and removal of ever larger surface anomalies to obtain optimal separation is of interest. At up to now studies, large deviation of primarily original signal has been prevented. In this paper controlling factors which limit the overall deviation of transformed signal from the original one have been replaced with two new parameters that simultaneously cause extracting the maximum surplus signals, residuals, and also preserving the original form ever possible. Results of artificial models along with application of separation to real data indicate the usefulness of discrete stationary wavelet transform in order to optimal separation of anomalies with various wavelengths.

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Paper Citation


in Harvard Style

Mousavi N., E. Ardestani V. and Moosavi H. (2013). Effective Residual and Regional Gravity Anomaly Separation - Using 1-D & 2-D Stationary Wavelet Transform . In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: PRG, (ICPRAM 2013) ISBN 978-989-8565-41-9, pages 659-668. DOI: 10.5220/0004219806590668


in Bibtex Style

@conference{prg13,
author={Naeim Mousavi and Vahid E. Ardestani and Hassan Moosavi},
title={Effective Residual and Regional Gravity Anomaly Separation - Using 1-D & 2-D Stationary Wavelet Transform},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: PRG, (ICPRAM 2013)},
year={2013},
pages={659-668},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004219806590668},
isbn={978-989-8565-41-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: PRG, (ICPRAM 2013)
TI - Effective Residual and Regional Gravity Anomaly Separation - Using 1-D & 2-D Stationary Wavelet Transform
SN - 978-989-8565-41-9
AU - Mousavi N.
AU - E. Ardestani V.
AU - Moosavi H.
PY - 2013
SP - 659
EP - 668
DO - 10.5220/0004219806590668