Adaptive wavelet thresholding for image denoising and compression

The first part of this paper proposes an adaptive, data-driven threshold for image denoising via wavelet soft-thresholding. The threshold is derived in a Bayesian framework, and the prior used on the wavelet coefficients is the generalized Gaussian distribution (GGD) widely used in image processing...

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Veröffentlicht in:	IEEE transactions on image processing 2000-09, Vol.9 (9), p.1532-1546
Hauptverfasser:	Chang, S.G., Bin Yu, Vetterli, M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Artificial intelligence Bayesian analysis Bayesian methods Bit rate Compressing Computer science control theory systems Data compression Exact sciences and technology Gaussian distribution Image coding Image denoising Image processing Information, signal and communications theory Noise Noise reduction Parameter estimation Pattern recognition. Digital image processing. Computational geometry Quantization Signal processing Studies Telecommunications and information theory Thresholds Wavelet Wavelet coefficients
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