In this paper the problem of progressive lossless image coding is addressed. Many applications require a lossless compression of the image data. The possibility of progressive decoding of the bitstream adds a new func...
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ISBN:
(纸本)0780331222
In this paper the problem of progressive lossless image coding is addressed. Many applications require a lossless compression of the image data. The possibility of progressive decoding of the bitstream adds a new functionality for those applications using data browsing. In practice, the proposed scheme can be of intensive use when accessing large databases of images requiring a lossless compression (especially for medical applications). The international standard JPEG allows a lossless mode. It is based on an entropy reduction of the data using various kinds of estimators followed by source coding. The proposed algorithm works with a completely different philosophy summarized in the following four key points: 1) a perfect reconstruction hierarchical morphological subband decomposition yielding only integer coefficients, 2) prediction of the absence of significant information across scales using zerotrees of wavelet coefficients, 3) entropy-coded successive-approximation quantization, and 4) lossless data compression via adaptive arithmetic coding. This approach produces a completely embedded bitstream. Thus, it is possible to decode only partially the bitstream to reconstruct an approximation of the original image.
We construct a theory of binary wavelet decompositions of finite binary images, The new binary wavelet transform uses simple modulo-2 operations. It shares many of the important characteristics of the real wavelet tra...
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We construct a theory of binary wavelet decompositions of finite binary images, The new binary wavelet transform uses simple modulo-2 operations. It shares many of the important characteristics of the real wavelet transform, In particular, it yields an output similar to the thresholded output of a real wavelet transform operating on the underlying binary image. We begin by introducing a new binary field transform to use as an alternative to the discrete Fourier transform over GF(2). The corresponding concept of sequence spectra over GF(2) is defined. Using this transform, a theory of binary wavelets is developed in terms of two-band perfect reconstruction filter banks in GF(2). By generalizing the corresponding real field constraints of bandwidth, vanishing moments, and spectral content in the filters, we construct a perfect reconstruction wavelet decomposition, We also demonstrate the potential use of the binary wavelet decomposition in lossless image coding.
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