A simple, nonrigorous, synthetic view of wavelet theory is presented for both review and tutorial purposes. The discussion includes nonstationary signal analysis, scale versus frequency, wavelet analysis and synthesis...
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A simple, nonrigorous, synthetic view of wavelet theory is presented for both review and tutorial purposes. The discussion includes nonstationary signal analysis, scale versus frequency, wavelet analysis and synthesis, scalograms, wavelet frames and orthonormal bases, the discrete-time case, and applications of wavelets in signalprocessing. The main definitions and properties of wavelet transforms are covered, and connections among the various fields where results have been developed are shown.< >
We present planar curve descriptors that allow a hierarchical representation of curves. The descriptors are based on wavelet and multiwavelet transforms and they decompose a curve into components of different scales.
ISBN:
(纸本)0819429139
We present planar curve descriptors that allow a hierarchical representation of curves. The descriptors are based on wavelet and multiwavelet transforms and they decompose a curve into components of different scales.
The gyrator transform is a linear canonical transform, which generates the rotation of an optical signal in position-spatial frequency planes. Gyrator wavelet transform is a relatively newer optical information proces...
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The gyrator transform is a linear canonical transform, which generates the rotation of an optical signal in position-spatial frequency planes. Gyrator wavelet transform is a relatively newer optical information processing tool obtained by combining the gyrator transform with the wavelet transform. This combination provides multi-resolution analysis of an image which is twisted in spatial frequency planes. The proposed tool satisfies basic algebraic properties, such as the linearity property and Parseval's theorem. Considering the usefulness of this tool, here a study of features, applications, and implementation of the gyrator wavelet transform is presented. This work studies the features of the gyrator wavelet transform, which can find a role in different applications such as edge enhancement, image encryption, image hiding, and watermarking.
Fast algorithms performing time-scale analysis of multivariate functions are discussed. The algorithms employ univariate wavelets and involve a directional parameter, namely the angle of rotation. Both the rotation st...
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ISBN:
(纸本)0819429139
Fast algorithms performing time-scale analysis of multivariate functions are discussed. The algorithms employ univariate wavelets and involve a directional parameter, namely the angle of rotation. Both the rotation steps and the wavelet analysis/synthesis steps in the algorithms require a number of computations proportional to the number of data involved. The rotation and wavelet techniques are used for the segregation of wanted and unwanted components in a seismic signal. As an illustration, the rotation and wavelet methods are applied to a synthetic shot record.
We define and characterize a frame-like stable decomposition for subspaces in a separable Hilbert space. We call in pseudoframes for subspaces (PFFS). Properties of PFFS are discussed. A necessary and sufficient condi...
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ISBN:
(纸本)0819429139
We define and characterize a frame-like stable decomposition for subspaces in a separable Hilbert space. We call in pseudoframes for subspaces (PFFS). Properties of PFFS are discussed. A necessary and sufficient condition for the construction is provided. An analytical formula for the construction of PFFS is also derived. An example is studied both as a motivation of the theoretical study of such pseudoframes and as an actual construction. Potential applications of PFFS are discussed.
We present methods used to measure the information in anastronomical image, in both a statistical and a deterministic way. Wediscuss the wavelet transform and noise modeling, and describe how tomeasure the information...
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We present methods used to measure the information in anastronomical image, in both a statistical and a deterministic way. Wediscuss the wavelet transform and noise modeling, and describe how tomeasure the information and the implications for object detection,filtering, and deconvolution. The perspectives opened up by the range ofnoise models, catering for a wide range of eventualities in physicalscience imagery and signals, and the new two-pronged but tightly coupledunderstanding of the concept of information have given rise to betterquality results in applications such as noise filtering, deconvolution,compression, and object (feature) detection. We have illustrated some ofthese new results in this article. The theoretical foundations of ourperspectives have been sketched out. The practical implications, too,are evident from the range of important signalprocessing problems whichwe can better address with this armoury of methods. The resultsdescribed in this work are targeted at information and at *** we have focused on experimental results in astronomical image andsignalprocessing, the possibilities are apparent in many otherapplication domains
High-resolution optical mapping is an emerging technique to record the activation and propagation of transmembrane potential on the surface of cardiac tissues. Important electrodynamic information previously not avail...
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ISBN:
(纸本)0819429139
High-resolution optical mapping is an emerging technique to record the activation and propagation of transmembrane potential on the surface of cardiac tissues. Important electrodynamic information previously not available from extracellular electric recording could be extracted from these detailed optical recordings. The noise contamination in the images is a major obstacle that prohibits higher level of information extraction. Because the patterns of interest contain sharp wavefronts and structures that we wish to detect and track in a series of: flames, we seek to perform denoising based on wavelet decomposition approaches. Among the wavelet denoise methods that were tested in this preliminary study, the wavelet packet produced the best results that could be extended to denoise the entire image sequence for multi-dimensional information processing.
The main contribution of this work is a new paradigm for image compression. We describe a new multi-layered representation technique for images. An image is encoded as the superposition of one main approximation, and ...
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ISBN:
(纸本)0819429139
The main contribution of this work is a new paradigm for image compression. We describe a new multi-layered representation technique for images. An image is encoded as the superposition of one main approximation, and a sequence of residuals. The strength of the multi-layered method comes from the fact that we use different bases to encode the main approximation and the residuals. For instance, we can use: - a wavelet basis to encode a coarse main approximation of the image, - wavelet packet bases to encode textured patterns, - brushlet bases to encode localized oriented textured features, etc.
We address the problem of improving the performance of wavelet based fractal image compression by applying efficient triangulation methods. We construct iterative function systems (IFS) in the tradition of Barnsley an...
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ISBN:
(纸本)0819429139
We address the problem of improving the performance of wavelet based fractal image compression by applying efficient triangulation methods. We construct iterative function systems (IFS) in the tradition of Barnsley and Jacquin, using non-uniform triangular range and domain blocks instead of uniform rectangular ones. We search for matching domain blocks in the manner of Zhang and Chen, performing a fast wavelet transform on the blocks and eliminating low resolution mismatches to gain speed. We obtain further improvements by the efficiencies of binary triangulations (including the elimination of affine and symmetry calculations and reduced parameter storage), and by pruning the binary tree before construction of the IFS. Our wavelets are triangular Haar wavelets and "second generation" interpolation wavelets as suggested by Sweldens' recent work.
Steganography plays a big role in secret communication by concealing secret information in the carrier. This paper presents a graph signalprocessing-based robust image steganography technique for posting images over ...
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Steganography plays a big role in secret communication by concealing secret information in the carrier. This paper presents a graph signalprocessing-based robust image steganography technique for posting images over social networks. In the embedding, we first obtained a scrambled version of the secret image using quantum scrambling. Next, we applied graph wavelet transformation on both the cover image and scrambled secret image followed by alpha (alpha) blending on both imagesignals (cover imagesignal and scrambled imagesignal). Finally, inverse graph wavelet transformation of the resulting image was undertaken to obtain the stego image. In this paper, the use of graph wavelet transformation improved interpixel correlation, which resulted in the excellent visual quality of both the stego image and the extracted secret image. Our experiments show that the picture quality of both the cover image and the stego image is exactly the same.
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