We give many examples of bivariate nonseparable compactly supported orthonormal wavelets which are supported over [0,3]x[0,3]. The Holder continuity properties of these wavelets are studied.
ISBN:
(纸本)0819425915
We give many examples of bivariate nonseparable compactly supported orthonormal wavelets which are supported over [0,3]x[0,3]. The Holder continuity properties of these wavelets are studied.
We discover a new relationship between two seemingly different image modeling methodologies;the Besov space theory and the wavelet-domain statistical image models. Besov spaces characterize the set of real-world image...
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ISBN:
(纸本)0819432997
We discover a new relationship between two seemingly different image modeling methodologies;the Besov space theory and the wavelet-domain statistical image models. Besov spaces characterize the set of real-world images through a deterministic characterization of the image smoothness, while statistical image models capture the probabilistic properties of images. By establishing a relationship between the Besov norm and the normalized likelihood function under an independent wavelet domain generalized Gaussian model, we obtain a new interpretation of the Besov norm which provides a natural generalization of the theory for practical imageprocessing. Based on this new interpretation of the Besov space, we propose a new image denoising algorithm based on projections onto the convex sets defined in the Besov space: After pointing out the limitations of Besov spaces, we propose possible generalizations using more accurate image models.
In this paper, we present a new method of image coding using two popular imaging tools, Zernike moments and wavelets. The main idea is that we can produce appropriate image descriptors by involving an appropriate numb...
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ISBN:
(纸本)0780375033
In this paper, we present a new method of image coding using two popular imaging tools, Zernike moments and wavelets. The main idea is that we can produce appropriate image descriptors by involving an appropriate number of moments, compressed in a form suitable to represent an image with low reconstruction error for pattern recognition applications. At this point the concept of wavelet compression is involved, which has already been discussed in many technical papers. We use an existent wavelet based compression algorithm, to compress not the 2-D image, but the resulted moment based 1-D signal. So, using this formulation we can achieve a compressed representation of the image, suitable for pattern recognition purposes and image retrieval tasks. It is very important to notice here the ability of Zernike moments to provide a very high level of image reconstruction, using the inverse wavelet transform, establishing a useful method.
In this work, we introduce a nonlinear geometric transform, called peak transform, for efficient image representation and coding. Coupled with wavelet transform and subband decomposition, the peak transform is able to...
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ISBN:
(纸本)9781424414369
In this work, we introduce a nonlinear geometric transform, called peak transform, for efficient image representation and coding. Coupled with wavelet transform and subband decomposition, the peak transform is able to significantly reduce signal energy in high-frequency subbands and achieve a significant transform coding gain. This has important applications in efficient data representation and compression. Based on peak transform (PT), we design an image encoder, called PT encoder, for efficient image compression. Our extensive experimental results demonstrate that, in wavelet-based subband decomposition, the signal energy in high-frequency subbands can be reduced by up to 60% if a peak transform is applied. The PT image encoder outperforms state-of-the-art JPEG2000 and H.264 (INTRA) encoders by up to 2-3 dB in PSNR (peak signal-to-noise ratio), especially for images with a significant amount of high-frequency components.
The problem of image enhancement arises in many applications such as scanners, copiers and digital cameras. Enhancement often includes a denoising and a deblurring or sharpening step. Similar to image compression, sta...
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ISBN:
(纸本)0780362985
The problem of image enhancement arises in many applications such as scanners, copiers and digital cameras. Enhancement often includes a denoising and a deblurring or sharpening step. Similar to image compression, state-of-the-art denoising techniques use wavelet bases instead of Fourier bases since wavelet domain processing provides local adaptation in smooth and non-smooth parts due to the theoretical link between wavelets and smoothness spaces. In this paper the same smoothness spaces are used to propose a way of performing Sharpening and Smoothing of signals with wavelets (WSS) in Besov spaces. As an application the completely wavelet-based enhancement of a scanned document is discussed.
wavelet transform coding image compression is applied to two raw seismic data sets. The parameters of filter length, depth of decomposition, and quantization method are varied through 36 parameter settings and the rat...
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ISBN:
(纸本)0819425915
wavelet transform coding image compression is applied to two raw seismic data sets. The parameters of filter length, depth of decomposition, and quantization method are varied through 36 parameter settings and the rate-distortion relation is plotted and fitted with a line. The lines are compared to judge which parameter setting produces the highest quality for a given compression ratio on the sample data. It is found that long filters, moderate decomposition depths, and frequency-weighted, variance-adjusted quantization yield the best results.
We investigate the application of adaptive wavelets for the representation and classification of signals in digitized speech and medical images. A class of wavelet basis functions are used to extract features from the...
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ISBN:
(纸本)0819425915
We investigate the application of adaptive wavelets for the representation and classification of signals in digitized speech and medical images. A class of wavelet basis functions are used to extract features from the regions of interest. These features are then used in an artificial neural network to classify the region as containing the desired object or belonging to the background clutter. The dilation and shift parameters of the wavelet functions are not fixed. These parameters are included in the training scheme. In this way the wavelets are adaptive to the expected shape and size of the signals. The results indicate that adaptive wavelet functions may outperform the classical fixed wavelet analysis in detection of subtle objects.
Bivariate box splines for image interpolation, enhancement, digital filter design, subband coding bank, hexagonal filtering will be discussed. Some existing and new results will be presented. A computational method fo...
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ISBN:
(纸本)0819422134
Bivariate box splines for image interpolation, enhancement, digital filter design, subband coding bank, hexagonal filtering will be discussed. Some existing and new results will be presented. A computational method for box spline image interpolation and box spline digital filters are included.
Transform-based image coders exploit the information packing ability of some mathematical transforms in order to reduce the number of significant transform coefficients needed to accurately represent an image. Large c...
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ISBN:
(纸本)0819422134
Transform-based image coders exploit the information packing ability of some mathematical transforms in order to reduce the number of significant transform coefficients needed to accurately represent an image. Large coefficients are often associated with those regions where an image changes a lot, such as the boundaries between objects with differing visual characteristics. One way to reduce the number of significant transform coefficients is to segment an image into regions of similarity and then apply the transform to each region separately. We propose a novel image compression technique which first segments an image into arbitrary regions and then applies a region-adapted wavelet transform to each region.
The primary goal of this paper is to give examples of the recently developed (finite-field) wavelet coding method by studying the encoder and decoder for some half-rate codes. We propose a decoding methodology based o...
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ISBN:
(纸本)0780370414
The primary goal of this paper is to give examples of the recently developed (finite-field) wavelet coding method by studying the encoder and decoder for some half-rate codes. We propose a decoding methodology based on estimating the polyphase components of the channel error pattern. To demonstrate the striking computational savings of the wavelet coding method over alternatives, we show that bounded-distance decoding of the (24,12,8) Golay code requires only weight computations (or at the worst case, it needs a cyclic lookup table of table size 12). The simplicity and computational savings that finite field wavelets offer for the encoding and decoding of wavelet block codes indicate their powerful capacities for error control coding applications.
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