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Proceedings Paper

Wavelet-transform-based image processing techniques in nonimage data sets
Author(s): Fotios P. Kourouniotis; Arun K. Majumdar
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Paper Abstract

Certain image processing methods such as filter banks, wavelet packets, and multiresolution analysis have been extensively used for efficiently decomposing, de-noising, compressing and reconstructing images in recent years1. While these methods have been applied primarily in images, their usefulness for decomposing and de-noising sets of measured data has not been thoroughly established yet. This paper will explore the potential of the application of image processing methods in non-image data sets. It is shown that filter banks can be potentially used to process and de-noise seismic data sets successfully. The idea is to treat a seismogram like a "conventional" image and extract certain features in a similar fashion to traditional image processing techniques. In this particular paper, the usage and application of wavelet bases will be explored.

Paper Details

Date Published: 22 October 2004
PDF: 7 pages
Proc. SPIE 5557, Optical Information Systems II, (22 October 2004); doi: 10.1117/12.563204
Show Author Affiliations
Fotios P. Kourouniotis, Univ. of Wyoming (United States)
Arun K. Majumdar, LCResearch, Inc. (United States)

Published in SPIE Proceedings Vol. 5557:
Optical Information Systems II
Bahram Javidi; Demetri Psaltis, Editor(s)

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