Math @ Duke

Publications [#287133] of Ingrid Daubechies
Papers Published
 Antonini, M; Barlaud, M; Mathieu, P; Daubechies, I, Image coding using vector quantization in the wavelet transform domain,
Icassp, Ieee International Conference on Acoustics, Speech and Signal Processing Proceedings, vol. 4
(December, 1990),
pp. 22972300, IEEE [doi]
(last updated on 2019/05/21)
Abstract: A twostep scheme for image compression that takes into account psychovisual features in space and frequency domains is proposed. A wavelet transform is first used in order to obtain a set of orthonormal subclasses of images; the original image is decomposed at different scales using a pyramidal algorithm architecture. The decomposition is along the vertical and horizontal directions and maintains the number of pixels required to describe the image at a constant. Second, according to Shannon's ratedistortion theory, the wavelet coefficients are vector quantized using a multiresolution codebook. To encode the wavelet coefficients, a noiseshaping bitallocation procedure which assumes that details at high resolution are less visible to the human eye is proposed. In order to allow the receiver to recognize a picture as quickly as possible at minimum cost, a progressive transmission scheme is presented. The wavelet transform is particularly well adapted to progressive transmission.


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