In this paper, an innovative algorithm for object segmentation and contour extraction algorithm is proposed, where the active contour evolution based on Mumford-Shah model is performed on coarse-to-fine approach spann...
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ISBN:
(纸本)0780374886
In this paper, an innovative algorithm for object segmentation and contour extraction algorithm is proposed, where the active contour evolution based on Mumford-Shah model is performed on coarse-to-fine approach spanned by wavelet. transform. The multilevel active contour model consists of three, main parts: 1) wavelet : decomposition for obtaining Multi-scale image;2) in the top-level imagewavelet-based edge detection to get an initial evolving, contour (initialization procedure);3) evolving contour based on Mumford-Shah model in each level, from top level to down level. The experiments and analysis demonstrate that the whole calculation on multi-objects contour extraction can be greatly decreased by the benefit of coarse-to-fine strategy and ideal noise resistance ability can also be expected in this algorithm.
In this work we present a technique based on wavelet analysis for EEGs processing of epileptic patients explored with scalp electrodes. Our aims is to provide a contribution to the automatic treatment of EEGs in the f...
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ISBN:
(纸本)0819437646
In this work we present a technique based on wavelet analysis for EEGs processing of epileptic patients explored with scalp electrodes. Our aims is to provide a contribution to the automatic treatment of EEGs in the following areas of clinical applications: detection of transients, data reduction in long-term records and tracking of crisis propagation. We show the results obtained with the proposed method applied to several EEGs records.
In this work, a new image watermarking algorithm on colour images is proposed. The proposed algorithm divides a cover image into three colour bands of red, green and blue. Then the following tasks are done on all thre...
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ISBN:
(纸本)9781509064946
In this work, a new image watermarking algorithm on colour images is proposed. The proposed algorithm divides a cover image into three colour bands of red, green and blue. Then the following tasks are done on all three channels separately. First, Each colour band is divided into patches of small sizes then the entropy of each patch is calculated. At this step a threshold is found based on the average entropy of all patches and following is applied to all patches which have entropy lower than the threshold. A wavelet representation of each patch are given by applying a discrete wavelet transform. Then Singular value decomposition, orthogonal-triangular decomposition, and a chirp z-transform are used to embed a watermark on the cover image. Several signalprocessing attacks are applied on watermarked images in order to robustness of the algorithm. The Proposed algorithm is compared with one conventional and two state-of-the-art algorithms. Experimental results show superiority of the proposed algorithm compare with other algorithm in the area of image watermarking.
We discuss a method for initializing the multi-wavelet decomposition algorithm by pre-filtering. The proposed pre-filtering operation projects the input signal into the space defined by the multi-scaling function asso...
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ISBN:
(纸本)0819425915
We discuss a method for initializing the multi-wavelet decomposition algorithm by pre-filtering. The proposed pre-filtering operation projects the input signal into the space defined by the multi-scaling function associated with the multi-wavelet. Since the approach is projection based, it is guaranteed to always have a solution. The space in which the original signal is contained is defined by multiple generating functions, making this work a generalization of our previous results.
A novel method for the automatic generation of a facial texture is proposed in this paper. Multiple pictures from the individual are combined to create the texture using a wavelet-based technique. The different tasks ...
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ISBN:
(纸本)9781424404810
A novel method for the automatic generation of a facial texture is proposed in this paper. Multiple pictures from the individual are combined to create the texture using a wavelet-based technique. The different tasks involved in the proposed method include: scaling, histogram equalization, deformation and merging. A set of particular feature points of the MPEG-4 standard for multimedia applications is used in the above mentioned tasks. In the merging stage, wavelet multiresolution decomposition of the images and filtering of the wavelet coefficients are performed to obtain a seamless texture. Finally, the resulting texture is mapped onto a 3D head model which has been adapted to the particular individual based on the same pictures. Since the proposed method relies on the MPEG-4 Facial and Body Animation (FBA) standard, it can be easily integrated with applications using the same standard.
Multichannel imaging systems provide several observations of the same scene which are often corrupted by additive noise. In this paper, we are interested in multispectral image denoising in the wavelet domain. We adop...
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Multichannel imaging systems provide several observations of the same scene which are often corrupted by additive noise. In this paper, we are interested in multispectral image denoising in the wavelet domain. We adopt a multivariate approach in order to exploit the correlations existing between the different spectral components. Our main contribution is the application of Stein's principle to build a new estimator for arbitrary multichannel images embedded in Gaussian noise. Simulation tests carried out on multispectral satellite images show that the proposed method outperforms conventional wavelet shrinkage techniques.
Shift variance and poor directional selectivity, two major disadvantages of the discrete wavelet transform, have previously been circumvented either by using highly redundant, non-separable wavelet transforms or by us...
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ISBN:
(纸本)0780370414
Shift variance and poor directional selectivity, two major disadvantages of the discrete wavelet transform, have previously been circumvented either by using highly redundant, non-separable wavelet transforms or by using restrictive designs to obtain a pair of wavelet trees with a transform-domain redundancy of 4.0 in 2D. In this paper, we demonstrate that excellent shift-invariance properties and directional selectivity may be obtained with a transform-domain redundancy of only 2.67 in 2D. We achieve this by projecting the wavelet coefficients from Selesnick's almost shift-invariant, double-density wavelet transform so as to separate approximately the positive and negative frequencies, thereby increasing directionality. Subsequent decimation and a novel inverse projection maintain the low redundancy while ensuring perfect reconstruction. Although our transform generates complex-valued coefficients allowing processing capabilities that are impossible with real-valued coefficients, it may be implemented with a fast algorithm that uses only real arithmetic. To demonstrate the efficacy of our new transform, we show that it achieves state-of-the-art performance in a seismic image-processing application.
A scheme for extracting morphological information from images through a edge oriented wavelet decomposition is proposed. Multiresolution edge patterns extracted in the wavelet transform domain are represented by param...
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ISBN:
(纸本)0819432997
A scheme for extracting morphological information from images through a edge oriented wavelet decomposition is proposed. Multiresolution edge patterns extracted in the wavelet transform domain are represented by parameterized segments. Tracking these segments across consecutive frames of a sequence leads to a parametric cynematic echaracterization of the content of a video sequence, suited for high level syntactic processing.. Parameterized images are visualizable by means of the inverse wavelet transform.
We introduce in this paper the notion of wavelet-Karhunen-Loeve transform (WT-KLT) and apply it to the problem of noise removal. Decorrelating first the data in the spatial domain using the WT and afterwards using the...
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ISBN:
(纸本)0819437646
We introduce in this paper the notion of wavelet-Karhunen-Loeve transform (WT-KLT) and apply it to the problem of noise removal. Decorrelating first the data in the spatial domain using the WT and afterwards using the KLT in spectral domain allows us to derive a robust noise modeling in the WT-KLT space, and hence to filter the transformed data in an efficient way. Experiments are performed in order to derive (i) the best way to calculate the covariance matrix in the case of noisy data, (ii) the best method to correct the noisy WT-KLT coefficients. Finally we investigate if the curvelet transform could be an alternative to the wavelet transform for color image filtering.
In this paper, we describe about a triangular lattice structuring method for 3-D polygonal mesh data and a shape-adaptive wavelet transform of the structured geometry and textural data. Efficient representations of a ...
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ISBN:
(纸本)0780376226
In this paper, we describe about a triangular lattice structuring method for 3-D polygonal mesh data and a shape-adaptive wavelet transform of the structured geometry and textural data. Efficient representations of a 3-D object data has attracted wide attention for transmission and storage of computer graphics data and interactive design in manufacturing. Polygonal mesh data, which consist of connectivity information, geometry data and textural data, are often used for representing a 3-D object in many applications. We propose a method for structuring the polygonal mesh data on a triangular lattice plane with expanded nodes. And a shape-adaptive wavelet coding method is applied to the structured geometry data considering the expanded nodes. Experimental results show that the proposed method gives better coding performance than the Topologically Assisted Geometry Compression scheme.
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