On the base of local criteria of processing quality, a class of local adaptive linear filters for image restoration and enhancement is introduced. the filters work in a running window in the domain of DFT of DCT and h...
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ISBN:
(纸本)0819422134
On the base of local criteria of processing quality, a class of local adaptive linear filters for image restoration and enhancement is introduced. the filters work in a running window in the domain of DFT of DCT and have O (size of the window) computational complexity thanks to recursive algorithms of running DFT and DCT. the filter design and the recursive computation of running DCT are outlined and filtering for edge preserved noise suppression, blind image restoration and enhancement is demonstrated.
Blocking artifacts are the most objectionable drawback of block-based image and video coders. We describe a novel technique for removing blocking artifacts via multiscale edge processing. the new technique exploits th...
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ISBN:
(纸本)0819422134
Blocking artifacts are the most objectionable drawback of block-based image and video coders. We describe a novel technique for removing blocking artifacts via multiscale edge processing. the new technique exploits the advantages of an invertible multiscale edge representation from which the block edges can be easily identified and removed. By virtue of the multiscale edge processing one is able to deblock images effectively without blurring perceptually important features or introducing new artifacts. We present the deblocking algorithm with experimental results and a discussion.
Orthogonal, semiorthogonal and biorthogonal wavelet bases are special cases of oblique multiwavelet bases. One of the advantage of oblique multiwavelets is the flexibility they provide for constructing bases with cert...
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ISBN:
(纸本)0819422134
Orthogonal, semiorthogonal and biorthogonal wavelet bases are special cases of oblique multiwavelet bases. One of the advantage of oblique multiwavelets is the flexibility they provide for constructing bases with certain desired shapes and/or properties. the decomposition of a signal in terms of oblique wavelet bases is still a perfect reconstruction filter bank. In this paper, we present several examples that show the similarity and differences between the oblique and other types of wavelet bases. We start withthe Haar multiresolution to illustrate several examples of oblique wavelet bases, and then use the Cohen-Daubechies-Plonka multiscaling function to construct several oblique multiwavelets.
We introduce a general framework for computing the continuous wavelet transform (CWT). Included in this framework is an FFT implementation as well as fast algorithms which achieve O(1) complexity per wavelet coefficie...
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ISBN:
(纸本)0819422134
We introduce a general framework for computing the continuous wavelet transform (CWT). Included in this framework is an FFT implementation as well as fast algorithms which achieve O(1) complexity per wavelet coefficient. the general approach that we present allows a straight forward comparison among a large variety of implementations. In our framework, computation of the CWT is viewed as convolving the input signal withwavelet templates that are the oblique projection of the ideal wavelets into one subspace orthogonal to a second subspace. We present this idea and discuss and compare particular implementations.
We present examples of a new type of wavelet basis functions that are orthogonal across shifts, but not across scales. the analysis functions are low order splines while the synthesis functions are polynomial splines ...
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ISBN:
(纸本)0819422134
We present examples of a new type of wavelet basis functions that are orthogonal across shifts, but not across scales. the analysis functions are low order splines while the synthesis functions are polynomial splines of higher degree n2. the approximation power of these representations is essentially as good as that of the corresponding Battle- Lemarie orthogonal wavelet transform, withthe difference that the present wavelet synthesis filters have a much faster decay. this last property, together withthe fact that these transformation s are almost orthogonal, may be useful for image coding and data compression.
Multiresolution representation of images provides a flexible tool for information rate control in video coding for transmission and storage purposes. In this work, the different spatial resolution capability of the hu...
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ISBN:
(纸本)0819422134
Multiresolution representation of images provides a flexible tool for information rate control in video coding for transmission and storage purposes. In this work, the different spatial resolution capability of the human visual system withthe angular displacement from the foveal line of sight is exploited. When the region of interest of the observer can be determined with sufficient reliability, the resolution is regulated according to the expected receptive resolution. this leads to significant bitrate savings in some typical applications.
Multiwavelet transforms are a new class of wavelet transforms that use more than one prototype scaling function and wavelet in the multiresolution analysis/synthesis. the popular Geronimo-Hardin-Massopust multiwavelet...
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ISBN:
(纸本)0819422134
Multiwavelet transforms are a new class of wavelet transforms that use more than one prototype scaling function and wavelet in the multiresolution analysis/synthesis. the popular Geronimo-Hardin-Massopust multiwavelet basis functions have properties of compact support, orthogonality, and symmetry which cannot be obtained simultaneously in scalar wavelets. the performance of multiwavelets in still image compression is studied using vector quantization of multiwavelet subbands with a multiresolution codebook. the coding gain of multiwavelets is compared withthat of other well-known wavelet families using performance measures such as unified coding gain. Implementation aspects of multiwavelet transforms such as pre-filtering/post-filtering and symmetric extension are also considered in the context of image compression.
the performance of wavelet compression algorithms is generally judged solely as a function of the compression ratio and the vidual artifacts which are perceivable in the reconstructed image. the problem then becomes o...
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ISBN:
(纸本)0819422134
the performance of wavelet compression algorithms is generally judged solely as a function of the compression ratio and the vidual artifacts which are perceivable in the reconstructed image. the problem then becomes one of obtaining the best compression with fewest visible artifacts--a very subjective measure. Our wavelet compression algorithm uses an information theoretic analysis for the design of the compression maps. We have previously shown that maximizing the information for a given visual communication channel also maximizes the visual quality of the restored image. We utilize this to design quantization maps which maximize information for a given compression ratio. Hence we are able to design quantization maps which maximize the restorability of an image--i.e. the information content, the image quality, and the mean-square difference fidelity--for a given compression ratio.
Fractal interpolation functions have become popular after the works of *** and his co-authors on iterated function systems and their applications to data compression3'4. Here, we consider the following problem: gi...
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ISBN:
(纸本)0819422134
Fractal interpolation functions have become popular after the works of *** and his co-authors on iterated function systems and their applications to data compression3'4. Here, we consider the following problem: given a set of values of a fractal interpolation function, recover the contractive affine mappings generating this function. the suggested solution is based on the connection, which is established in the work, between the maxima skeleton of wavelet transform of the function and positions of the fixed points of the affine mappings in question.
Keywords: Fractal interpolation,wavelets, data compression.
Mallat's pyramid algorithm relates the scaling coefficients of a function at one level to the scaling and wavelet coefficients at lower levels. In practice, the scaling coefficients are estimated at some level m, ...
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ISBN:
(纸本)0819422134
Mallat's pyramid algorithm relates the scaling coefficients of a function at one level to the scaling and wavelet coefficients at lower levels. In practice, the scaling coefficients are estimated at some level m, and the algorithm is used to produce estimates of the scaling and wavelet coefficients at lower levels. Initial errors propagate to lower level estimates. this paper descries conditions under which this process generates estimates which are uniformly reliable at a particular level, and under which the errors at that level tend uniformly to zero as m increases.
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