Wavelet-transform-based image processing techniques in nonimage data sets

Fotios P. Kourouniotis; Arun K. Majumdar

doi:10.1117/12.563204

22 October 2004 Wavelet-transform-based image processing techniques in nonimage data sets

Fotios P. Kourouniotis, Arun K. Majumdar

Proceedings Volume 5557, Optical Information Systems II; (2004) https://doi.org/10.1117/12.563204
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

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.

Citation Download Citation

Fotios P. Kourouniotis and Arun K. Majumdar "Wavelet-transform-based image processing techniques in nonimage data sets", Proc. SPIE 5557, Optical Information Systems II, (22 October 2004); https://doi.org/10.1117/12.563204

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