Adaptive threshold selection technique for denoising in dithered quantizers

Samuel Peter Kozaitis; Hemen Goswami

doi:10.1117/12.421195

26 March 2001 Adaptive threshold selection technique for denoising in dithered quantizers

Proceedings Volume 4391, Wavelet Applications VIII; (2001) https://doi.org/10.1117/12.421195
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

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.

Citation Download Citation

Samuel Peter Kozaitis and Hemen Goswami "Adaptive threshold selection technique for denoising in dithered quantizers", Proc. SPIE 4391, Wavelet Applications VIII, (26 March 2001); https://doi.org/10.1117/12.421195

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