In this paper, we present a fast algorithm for the computation of the wavelet transform in higher dimensional Euclidean space Rn with arbitrary shaped wavelets. the algorithm is a direct consequence of the convolution...
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In this paper, we present a fast algorithm for the computation of the wavelet transform in higher dimensional Euclidean space Rn with arbitrary shaped wavelets. the algorithm is a direct consequence of the convolution property of the Radon transform and shows significant improvement in speed. We also present a novel approach for the computation of the Daubechies type wavelet transform under the Radon transform domain where the n-dimensional multiresolution Analysis (MRA) is reduced to one-dimensional MRA. We found applications of this approach on, for instance, multiresolution reconstruction of the tomographic image withthe standard methods of denoising, where determination of wavelet coefficients is required under the Radon transform domain. Along withthe possibility of reducing samples angularly with decreasing resolution, the efficiency can be further improved. Besides, extra property such as 'rotated' wavelet can be easily implemented withthis algorithm.
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.
the proceedings contains 443 papers from the 1995 IEEE Engineering in Medicine and Biology Annual conference. Topics discussed include: electroencephalographic and magnetoencephalographic signalprocessing;autoregress...
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the proceedings contains 443 papers from the 1995 IEEE Engineering in Medicine and Biology Annual conference. Topics discussed include: electroencephalographic and magnetoencephalographic signalprocessing;autoregressive techniques in signalprocessing;signal filtering techniques;visual evoked potentials;signal estimation;time-frequency analysis and applications;medical image visualization;wavelet-based signal analysis;signal detection and discrimination using wavelets;neuromuscular stimulation and recording;magnetic stimulation;bladder, pain and tactile stimulation;implantable muscle electrodes;wheelchair propulsion kinematics and dynamics;and tele-surgical manipulation and ergonomic simulation.
Some signalprocessingapplications require memory modules with very fast access along predefined scan patterns. If this requirement only holds for standard raster scan (imageprocessing) the simple solution of readin...
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ISBN:
(纸本)0819418137
Some signalprocessingapplications require memory modules with very fast access along predefined scan patterns. If this requirement only holds for standard raster scan (imageprocessing) the simple solution of reading in parallel a number of slower memory chips and using a fast parallel to serial converter is enough. this paper focuses on the problems which appear when more different fast scans patterns are required. In this case the mapping of the data in the memory chips is analyzed by using a combinatorial theory setting. We prove that a mapping which allows two different predefined scan patterns does always exist. For more than two different predefined scans our formalism allows one to construct a mapping, if it does exist. the paper presents several examples with 2 and 4 scan patterns.
this paper proposes a new family of perfect reconstruction (PR) linear phase filter banks called the generalized lapped transform (GLT). the GLT differs from the traditional lapped orthogonal transform (LOT) [1] in th...
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this paper proposes a new family of perfect reconstruction (PR) linear phase filter banks called the generalized lapped transform (GLT). the GLT differs from the traditional lapped orthogonal transform (LOT) [1] in that it is nonorthogonal and hence offers more freedom to avoid blocking effects and improve the coding gain. Since the GLT can also be viewed as a generalization of the traditional discrete cosine transform (DCT), fast algorithms [2-4] for their implementation are also available.
Texture has found many applications in computer vision. Examples where texture analysis methods are being used include: (i) classifying images and browsing images based on their texture;(ii) segmenting an input image ...
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Most recent advances in fractal image coding have been concentrating on better adaptive coding algorithms, on extending the variety of the blocks and on search strategies to reduce the encoding time. Very little has b...
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A novel intraframe source coding algorithm suitable for the recording of digital high definition television signals is presented. A multi-layered, hierarchical description of the source signal is obtained by means of ...
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A novel intraframe source coding algorithm suitable for the recording of digital high definition television signals is presented. A multi-layered, hierarchical description of the source signal is obtained by means of a quad-tree, half-band wavelet transform. this transform decomposes the input signal into a collection of spectrally non-overlapping subbands. Individual subbands are quantised and entropy coded by using a novel predictive arithmetic coding technique. the algorithm is tuned to achieve bit-rate reduction ratios in the range 8:1-4:1 which is most useful for recording applications. Results obtained from simulating the coding algorithm, show noticeable improvement over the current state-of-the-art international standard algorithm for still picture encoding both in terms of subjective quality and of measured mean-square error.< >
We propose a Markov Random Field image model formulated using both low-order and high-order interactions of the pixels for piecewise smoothimage reconstruction. We discuss and compare the applications of two Bayes es...
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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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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.
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