作者：
Lu, JApple Computer
Compression and Signal Processing Dept. MS 302-3MT Cupertino CA 95014 2 Infinite Loop United States
This paper studies the algorithms that reconstruct a signal from its wavelet extrema representation. We show that the existing reconstruction algorithms are inadequate in assuring a consistent reconstruction. We furth...
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ISBN:
(纸本)0819425915
This paper studies the algorithms that reconstruct a signal from its wavelet extrema representation. We show that the existing reconstruction algorithms are inadequate in assuring a consistent reconstruction. We further propose a method that can be used with a number of existing algorithms to guarantee a consistent reconstruction. The new method provides a rigorous way to prevent artifacts resulting from the spurious wavelet extrema in the reconstructed signal.
This paper concentrates on how to construct wavelets according to the practical needs of computer vision and imageprocessing. At first, a theory for the construction of dyadic wavelets has been established. The resul...
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ISBN:
(纸本)0819424935
This paper concentrates on how to construct wavelets according to the practical needs of computer vision and imageprocessing. At first, a theory for the construction of dyadic wavelets has been established. The resulted dyadic wavelets possess zero-symmetric or zero-antisymmetric property, and can also be fastly decayed so that they are suitable for edge detection. Then an algebra approach for the construction of orthogonal wavelets is proposed. It facilitaes the selection of best wavelet for a given imageprocessing task such as image compression.
If G is an orthonormal system in IL2 then for any function g is an element of G the function g(2) is a probability density. In this paper we discuss the properties of wavelet based densities and corresponding random v...
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ISBN:
(纸本)0819425915
If G is an orthonormal system in IL2 then for any function g is an element of G the function g(2) is a probability density. In this paper we discuss the properties of wavelet based densities and corresponding random variables.
EMG signals can be considered as the sum of scaled and delayed versions of a single prototype. We have applied the Wavelet Transform choosing the mother wavelet so as to match the known shape of the basic component, a...
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ISBN:
(纸本)0819425915
EMG signals can be considered as the sum of scaled and delayed versions of a single prototype. We have applied the Wavelet Transform choosing the mother wavelet so as to match the known shape of the basic component, and have compared the results obtained with different wavelets. The results in terms of MUAP detection and resolution are very encouraging even in the presence of asymmetric shape and high levels of additive noise.
In this paper, the relationship between wavelet transform and Differential Mapping Singularities Theory (DMST) is discussed in the context of image compression. DMST maps 3-D surfaces accurately, with exact results, a...
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ISBN:
(纸本)0819425915
In this paper, the relationship between wavelet transform and Differential Mapping Singularities Theory (DMST) is discussed in the context of image compression. DMST maps 3-D surfaces accurately, with exact results, and to construct an image compression algorithm based on an expanded set of operations. This set includes shift, scaling rotation, and homogenous nonlinear transformations. This approach permits the mathematical description of a full set of singularities that describe edges and other specific points of objects. The edges and specific points (degenerate critical points) are the product of mapping smooth 3-D surfaces, which can be described by a simple set of polynomials that are suitable for image compression and Automatic Target Recognition (ATR). In signal and imageprocessing, wavelets have been used for several years to provide multi-resolution data representation [1] Originally, wavelets were developed for one-dimensional signal decomposition. Subsequently, they were generalized to 2-D image coding. Now, wavelet transform is used to hierarchically decompose an input signal into a series of lower resolution reference signals and associated detail signals. At each level, a reference signal and its associated detail signal contain information required to reconstruct the reference signal at the next higher resolution level. Efficient image coding is enabled by allocating the bandwidth according to the relative importance of information in the reference and detail signals, and then applying the next level of the lossy and lossless compression algorithm.
Given multiple images of a diffuse surface taken from the same point of view, a photometric approach yields the surface normals which provide a good representation for a 1-1 surface. This representation can be filtere...
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ISBN:
(纸本)0819425915
Given multiple images of a diffuse surface taken from the same point of view, a photometric approach yields the surface normals which provide a good representation for a 1-1 surface. This representation can be filtered and compressed using wavelets. In this work, two different applications based upon the wavelet approximations of the surface normals are presented. For the first application, surface reconstruction, compressed wavelet transforms of the images are used to reconstruct a surface. The surface shape is first interpolated from a three dimensional triangulated description, and then transformed into two and three images based solely upon the surface normals and the lighting direction. When the surface is compressed, the rational wavelets used in integrating the surface can produce singularities. A technique for handling compression of rational wavelets is presented. The second application is object differentiation, a subset of object recognition. The surface normals are used to derive the Gaussian curvature of an object. The Gaussian curvature is used as a primitive for classification. The actual object signature comes from the high magnitude coefficients in the Haar wavelet decomposition. By storing a library of objects indexed by extreme wavelet coefficients as opposed to the object name, a fast query can be performed to find a list of possible matches.
In this paper we show that if wavelet domain processing is used with digital restoration, then pixel-scale features can be restored exactly in the absence of noise. In the presence of noise results are similar, except...
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ISBN:
(纸本)0819425915
In this paper we show that if wavelet domain processing is used with digital restoration, then pixel-scale features can be restored exactly in the absence of noise. In the presence of noise results are similar, except for some noise-amplification and ringing artifacts. Wavelet domain modeling eliminates the need to discretize the image acquisition kernel and helps formulate image restoration as a discrete least squares problem. The performance of this technique is analyzed by model-based simulation using a comprehensive model to account for system blur at the image formation level, for the potentially important effects of aliasing, and for additive noise.
A complete wavelet-based image storage and indexing system for progressive coding, indexing, retrieval. and transmission of images over the network is proposed in this research. New wavelet domain features which inclu...
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ISBN:
(纸本)0819425915
A complete wavelet-based image storage and indexing system for progressive coding, indexing, retrieval. and transmission of images over the network is proposed in this research. New wavelet domain features which include subband significance, decomposition structure. luminance and chrominance histograms, and the significance map of the lowest frequency channel are used to achieve content-based indexing and retrieval. The proposed indexing features take into account of the color: brightness, texture, frequency, and spatial information of a given query image. All features can be naturally extracted as a byproduct during the image compression stage with wavelets. Since coding and indexing are integrated in an unified framework in the proposed system, the database management is greatly simplified. Extensive experimental results are given to demonstrate the retrieval performance of the new approach.
Wavelet transform is an efficient way to perform multiresolution signal decomposition with a good time and frequency resolution and simple generation of families of functions to generate bases of the space of square s...
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ISBN:
(纸本)085296692X
Wavelet transform is an efficient way to perform multiresolution signal decomposition with a good time and frequency resolution and simple generation of families of functions to generate bases of the space of square summable sequences. The basis functions used in the wavelet transform are all affine transformed versions of the original function. The compactly supported wavelets are defined from a scaling function that is the solution of a fractal-like equation. The multiresolution fractal coders lead to better results, both in terms of rate-distortion curves and visual quality.
A method which constructs local cosine bases with K-regular through cosine modulated 2-D perfect reconstruction filter bank is proposed. In this method, orthogonal wavelets with the number of arbitrary division in 2-D...
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ISBN:
(纸本)085296692X
A method which constructs local cosine bases with K-regular through cosine modulated 2-D perfect reconstruction filter bank is proposed. In this method, orthogonal wavelets with the number of arbitrary division in 2-D can be constructed if the polyphase components of the base lowpass filter have the relation of doubly-complementary and satisfy regular condition.
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