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26 March 2001 Adaptive threshold selection technique for denoising in dithered quantizers
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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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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