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Proceedings Paper

Adaptive threshold selection technique for denoising in dithered quantizers
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Paper Abstract

We described an adaptive denoising method to improve image quality in a wavelet-based image compression process that uses dithered quantization. In our method, the second-order moment of the quantization noise is made independent of the signal by random quantization. Then, the quantization noise is reduced by thresholding wavelet coefficients. We first obtained a fixed threshold using any known technique. Then, a neighborhood is searched for the optimal threshold to optimize some cost function.

Paper Details

Date Published: 26 March 2001
PDF: 7 pages
Proc. SPIE 4391, Wavelet Applications VIII, (26 March 2001); doi: 10.1117/12.421195
Show Author Affiliations
Samuel Peter Kozaitis, Florida Institute of Technology (United States)
Hemen Goswami, GE Harris Harmon Railway Technology (United States)


Published in SPIE Proceedings Vol. 4391:
Wavelet Applications VIII
Harold H. Szu; David L. Donoho; Adolf W. Lohmann; William J. Campbell; James R. Buss, Editor(s)

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