This paper deals with the analysis of time series with respect to certain known periodicities. In particular, we shall present a fast method aimed at detecting periodic behavior inherent in noisy data. The method is c...
详细信息
ISBN:
(纸本)0819429139
This paper deals with the analysis of time series with respect to certain known periodicities. In particular, we shall present a fast method aimed at detecting periodic behavior inherent in noisy data. The method is composed of three steps: 1. Non-noisy data are analyzed through spectral and wavelet methods to extract specific periodic patterns of interest. 2. Using these patterns, we construct an optimal piecewise constant wavelet designed to detect the underlying periodicities. 3. We introduce a fast discretized version of the continuous wavelet transform, as well as waveletgram averaging techniques, to detect occurrence and period of these periodicities. The algorithm is formulated to provide real time implementation. Our procedure is generally applicable to detect locally periodic components in signals s which can be modelled as s(t) = A(t)F(h(t)) + N(t) for t in I, (1) where F is a periodic signal, A is a non-negative slowly varying function, and h is strictly increasing with h' slowly varying. N denotes background activity. For example, the method can be applied in the context of epileptic seizure detection. In this case, we try to detect seizure periodics in EEG and ECoG data. In the case of ECoG data, N is essentially 1/f noise. In the case of EEG data and for t in I, N includes noise due to cranial geometry and densities.(1, 2) In both cases N also includes standard low frequency rhythms.(3) Periodicity detection has other applications including ocean wave prediction, cockpit motion sickness prediction, and minefield detection.
`Regularity' is a new criterion brought by wavelet theory over filter banks. It is therefore important to know whether this criterion is relevant for applications such as image compression, in comparison with othe...
详细信息
ISBN:
(纸本)0780309464
`Regularity' is a new criterion brought by wavelet theory over filter banks. It is therefore important to know whether this criterion is relevant for applications such as image compression, in comparison with other filter properties. The following problem is addressed: How do regularity, frequency selectivity and phase act upon the performance of a still image compression scheme using wavelet decomposition? Preliminary results are given for a simple compression scheme using orthonormal separable wavelet transforms, scalar quantization, rate/distortion optimization, various coding criteria, and a large number of `wavelet' filters with balanced regularity, frequency selectivity and phase.
This paper presents a satellite image compression scheme based on a post-processing of the wavelet transform of images. The bandelet transform is a directional post-processing of wavelet coefficients. Thanks to a low ...
详细信息
ISBN:
(纸本)9781424414833
This paper presents a satellite image compression scheme based on a post-processing of the wavelet transform of images. The bandelet transform is a directional post-processing of wavelet coefficients. Thanks to a low computational complexity, this transform is a good candidate for future on-board satellite image compression systems. First, we analyze the ability of the bandelets to exploit directional correlations between wavelet coefficients. This study leads to an improved post-processing with a better decorrelation of adjacent wavelet coefficients in the vertical or in the horizontal direction taking into account the wavelet subband orientations. To perform even better decorrelation, bases are also build by Principal Component Analysis (PCA). This results in an improved compression performance without increasing the computational complexity.
applications of image compression is important in terms of time and resource management considering factors such as require more time to send according to the size of image over the network and large amount of space i...
详细信息
ISBN:
(纸本)9781467373869
applications of image compression is important in terms of time and resource management considering factors such as require more time to send according to the size of image over the network and large amount of space is high dimensional data for storing images. In this study, a new approach can be using at image compression process will be introduced. Firstly, image subjected to discrete wavelet transform for extracting feature. Then multi-level threshold values will be find with Shanon entropy in the obtained image. The maximum value of objective function will be obtained with the help of cricket algorithm at the threshold values finding step. This algorithm is a meta-heuristic algorithm that based on population. The threshold values that obtained through algorithm using to compressing the images will be provided. At the end of the study, the image compression ratio, the proposed approach running on a standard test image will be given.
In this paper, a new approach for image edge detection using wavelet based ant colony optimization (ACO) is proposed. The proposed approach applies discrete wavelet transform (DWT) on the image. ACO is applied to the ...
详细信息
ISBN:
(纸本)9781479948741
In this paper, a new approach for image edge detection using wavelet based ant colony optimization (ACO) is proposed. The proposed approach applies discrete wavelet transform (DWT) on the image. ACO is applied to the generated four subbands (Approximation, horizontal, vertical, and diagonal) separately for edge detection. After obtaining edges from the 4 subbands, inverse DWT is applied to fuse the results into one image with same size as the original one. The proposed approach outperforms the conventional ACO approach.
In this paper, a wavelet packet transform wideband beamforming (WPTWB) is proposed. The proposed method employs wavelet packet analysis and synthesis filter banks, replacing the traditional analysis and synthesis filt...
详细信息
ISBN:
(纸本)9798350350920
In this paper, a wavelet packet transform wideband beamforming (WPTWB) is proposed. The proposed method employs wavelet packet analysis and synthesis filter banks, replacing the traditional analysis and synthesis filter banks used in subband beamforming, to achieve the decomposition and reconstruction of wideband signals. And the algorithm leverages the inherent multiresolution characteristics of the wavelet packet transform to capture both the nuanced details and broader generalizations present in broadband signals. Simulation experiments demonstrate the anti-interference ability and accuracy of the algorithm.
We propose an improved statistical characterization of the field of wavelet coefficients of natural images. Based on this characterization, we introduce Morphological Representation of wavelet Data (MRWD), a novel cod...
详细信息
ISBN:
(纸本)0780324323
We propose an improved statistical characterization of the field of wavelet coefficients of natural images. Based on this characterization, we introduce Morphological Representation of wavelet Data (MRWD), a novel coding framework for both image and video coding applications. MRWD departs from existing wavelet-based coders in its use of a radically different set of primitive operations -non-linear, morphological operations-, for efficiently encoding the wavelet data field. Simulation results are very encouraging: a preliminary algorithm based on the morphological data structure is able to achieve about 0.5 dB of gain in SNR over Shapiro's state-of-the-art zerotree-based wavelet coder [1] at a coding rate of 1 bpp for the 'Lenna' image.
Our goal in this article is to present a quantitative study about speech recognition and the inherent problems of its applications and the computer processing. Our approach is characterized by independent speaker and ...
详细信息
ISBN:
(纸本)0819425915
Our goal in this article is to present a quantitative study about speech recognition and the inherent problems of its applications and the computer processing. Our approach is characterized by independent speaker and we made use of pre-processing the concept as wavelets Transform and as pattern recognition an Artificial Neural Network (ANN - Multilayer Perceptron -Backpropagation Algorithm).
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...
详细信息
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.
We show how periodized wavelet packet transforms and periodized wavelet transforms can be implemented on a quantum computer. Surprisingly, we find that the implementation of wavelet packet transforms is less costly th...
详细信息
ISBN:
(纸本)0819432997
We show how periodized wavelet packet transforms and periodized wavelet transforms can be implemented on a quantum computer. Surprisingly, we find that the implementation of wavelet packet transforms is less costly than the implementation of wavelet transforms on a quantum computer.
暂无评论