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Proceedings Paper

Application of wavelet polynomial threshold for interpolation and denoising in bioimaging
Author(s): Michael Chan; Sushanth Sathyanarayana; David Akopian; Sos S. Agaian
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Paper Abstract

This paper demonstrates wavelet-denoising approach using polynomial threshold operators in 3-dimensional applications. This paper compares the efficacy of different denoising algorithms on 3D biomedical images using 3D wavelet transform. The denoising mechanism is demonstrated by mitigating noise of different variances using polynomial thresholding. Our approach is to apply a parameterized threshold and optimally choose the parameters for high performance noise suppression depending on the nature of the images and noise. Comparative studies in the wavelet domain conclude that the presented method is viable for 3D applications. It also confirms the feasibility in using the polynomial threshold operators as a wavelet-polynomial threshold based interpolation filter. The filter applied to assist three spatial-based interpolation algorithms (i.e. Nearest-neighbor, Bilinear, and Bicubic) and to a spectral wavelet-based interpolation algorithm. Simulation shows that the denoising using polynomial threshold operators mitigates distortions for the interpolation.

Paper Details

Date Published: 31 May 2011
PDF: 12 pages
Proc. SPIE 8063, Mobile Multimedia/Image Processing, Security, and Applications 2011, 80630Z (31 May 2011); doi: 10.1117/12.881304
Show Author Affiliations
Michael Chan, The Univ. of Texas at San Antonio (United States)
Sushanth Sathyanarayana, The Univ. of Texas at San Antonio (United States)
David Akopian, The Univ. of Texas at San Antonio (United States)
Sos S. Agaian, The Univ. of Texas at San Antonio (United States)


Published in SPIE Proceedings Vol. 8063:
Mobile Multimedia/Image Processing, Security, and Applications 2011
Sos S. Agaian; Sabah A. Jassim; Yingzi Du, Editor(s)

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