Title :
Application of Wavelet Transform in De-noising Geophysical Data
Author :
Shen, Guangrong ; Sarris, Apostolos
Author_Institution :
Lab. of Digital Agric., Shanghai Jiaotong Univ., Shanghai, China
fDate :
March 31 2009-April 2 2009
Abstract :
This paper presents a denoising scheme based on the wavelet transform for geophysical projecting data which are contaminated with various levels and types of local cultural noise which were responsible for hindering the valuable information obtained through shallow depth geophysical exploration of archaeological sites. Wavelet transform techniques were tested as a method for decomposing the original geophysical data in order to eliminate the noise levels inherent to the geophysical measurements. Unsupervised classification techniques were employed for the final fusion of different datasets originating from various surveys or processing procedures. The resulting images were able to enhance the subsurface targets, eliminating the noise levels and exploiting fully the properties of the geophysical techniques used. The scheme is particularly useful in minimizing the cultural noise as much as possible in order to allow the data to be interpreted accurately.
Keywords :
archaeology; geophysical signal processing; image classification; image denoising; image enhancement; image fusion; image reconstruction; wavelet transforms; archaeological site; de-noising geophysical projecting data; image enhancement; image fusion; image reconstruction; local cultural noise; shallow depth geophysical exploration; unsupervised classification technique; wavelet transform technique; Agriculture; Cultural differences; Discrete wavelet transforms; Frequency; Geophysical measurements; Magnetic noise; Noise level; Noise reduction; Wavelet domain; Wavelet transforms; Classification; Denoising; Fusion; Geophysical data; Greece; Wavelets;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.222