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共 4119 条记录，以下是101-110 订阅

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A multiscale geometric filter based on the wavelet transform

A multiscale geometric filter based on the wavelet transform

引用

4th conference on wavelet applications in signal and image processing

作者： Alparone, L Argenti, F Garzelli, A UNIV FLORENCE DEPT ELECT ENGNI-50139 FLORENCEITALY

ISBN: (纸本)0819422134

A viable approach to noise filtering in a spatially heterogeneous environment consists of considering a multiresolution representation of the noisy image, nd of applying a different adaptive filter to each layer. the wavelet decomposition has been widely employed, thanks to its capability to capture spatial features within frequency subbands. Geometric filter is a nonlinear local operator that exploits a morphologic approach to smooth noise using a complementary hull algorithm, which as the effect of gradually reducing the maximum curvature of the boundary of the grey-level profile along all of the 8-neighbor directions. the idea of the present scheme is to apply the complementary-hull algorithm to the different subbands into which the noisy image is decomposed. the hull is applied only on the direction along which the signal is structured. the number of iterations is adjusted to the SNR of the subbands, so as to preserve spatial details to the largest extent. Results and comparisons with the standard geometric filter are presented for images affected by synthetic multiplicative noise. ©2005 Copyright SPIE - the International Society for Optical Engineering.

关键词： image processing noise filtering adoptive filtering multiresolution analysis wavelet transform geometric filter SAR images speckle noise

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Target Recognition in ISAR images based on Relative Phases of Complex wavelet Coefficients and Sparse Classification 4

Target Recognition in ISAR Images based on Relative Phases o...

引用

4th International conference on Advanced Technologies for signal and image processing (ATSIP)

作者： Karine, Ayoub Toumi, Abdelmalek Khenchaf, Ali El Hassouni, Mohammed ENSTA Bretagne CNRS UMR 6285 Lab STICC Brest France Mohammed V Univ Rabat Fac Sci Rabat IT Ctr LRITCNRSTURAC 29 Rabat Morocco Mohammed V Univ Rabat FLSH Rabat IT Ctr LRITCNRSTURAC 29 Rabat Morocco

ISBN: (纸本)9781538652398

In this paper, we present a novel approach for radar automatic target recognition on inverse synthetic aperture radar (ISAR). this approach is composed by two complementary steps: feature extraction and recognition. For the feature extraction step, we adopt a statistical modeling of the ISAR image in the complex wavelet domain. For doing so, we apply the dual-tree complex wavelet transform (DT-CWT) for each ISAR image in the database. After that, the relative phases of the resulting complex coefficients are computed. these relative phases are after statistically modeled using the Von Mises distribution. the estimated statistical parameters compose the feature vector of the ISAR images. Regarding to the recognition rate, the constructed feature vector is fed into the sparse representation based classification (SRC). More precisely, the training feature vectors are used as the atoms of a dictionary. the test feature vector is recognized according to its sparse linear combination with the dictionary. Extensive experiments and comparisons with other methods on ISAR images database demonstrate the effectiveness of the proposed approach.

关键词： Automatic target recognition inverse synthetic aperture radar relative phase modeling sparse representation

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Scaled Gabor representation: A refined time-frequency decomposition

Scaled Gabor representation: A refined time-frequency decomp...

引用

4th conference on wavelet applications in signal and image processing

作者： Li, SD SAN FRANCISCO STATE UNIV COLL SCI & ENGNSAN FRANCISCOCA 94132

ISBN: (纸本)0819422134

A discrete scaled Gabor representation (SRG) is developed to meet the requirements of localized and refined time- frequency representation of signals. SGR generalizes the metaplectic structure by using windows' translation, modulation and dilation as synthesis waveforms. Fundamental features and importance of SGRs are discussed. We derive fast algorithms for the computation of related analysis sequences at different scales. An example of using SGRs for refined time-frequency representation is also demonstrated. A significant feature of SGRs also lies in the fact that they can be realized in a parallel FFT-based implementation structure.

关键词： scaled Gabor representation discrete multi-Gabor expansions combined wavelet-Gabor theory metaplectic structure

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A Hybrid RDWT-DCT and SVD Based Digital image Watermarking Scheme Using Arnold Transform 4

A Hybrid RDWT-DCT and SVD Based Digital Image Watermarking S...

引用

4th International conference on signal processing and Integrated Networks (SPIN)

作者： Gaur, Sachin Srivastava, Vinav Kumar Motilal Nehru Natl Inst Technol Dept Elect & Commun Engn Allahabad Uttar Pradesh India

ISBN: (纸本)9781509027972

In the present scenario Digital image water marking is a powerful method for solving the problems of tamper detection, rightful ownership, copyright protection and content authentication. In this paper a secure hybrid digital image watermarking scheme based on Redundant Discrete wavelet transform (RDWT), Discrete Cosine Transform (DCT) and Singular value decomposition (SVD) in zigzag order with Arnold transform is presented. Watermark image is scrambled by Arnold transform to boost up its secrecy and robustness. In presented scheme, a gray scale cover image is rearranged through zigzag sequence and then RDWT is implemented on this reordered cover image. After that DCT, SVD is implemented on mid and high frequency sub-bands (LH, LH, and HH) of cover image and modified the singular values of these sub-bands by embedding the scrambled gray scale watermark image. this presented scheme is more imperceptible and anenormous capacity due to the properties of RDWT and SVD. the benefit of the presented schemeis more robust and secured against various image processing attacks. Analysis and experimental outcomes show that the presented scheme is rich in terms of imperceptibility, robustness, capacity and security from earlier proposed schemes.

关键词： Redundant Discrete wavelet Transform Discrete Cosine Transform Singular Value Decomposition Arnold transforms NCC and PSNR

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A New Fast Approach for Skew Estimation using Moments and wavelet Transform 4

A New Fast Approach for Skew Estimation using Moments and Wa...

引用

International conference on image processing theory, Tools and applications (IPTA)

作者： Mehta, Sunita Walia, Ekta Dutta, Maitreyee Chandigarh Coll Engn & Technol OI Comp & ECE Chandigarh India South Asian Univ Dept Comp Sci New Delhi India NITTTR Dept Comp Sci Chandigarh India

ISBN: (纸本)9781479964635

In this paper, a new technique based on moments and wavelet transform is proposed to determine skew angle of document image. this technique is divided into two parts. Firstly, the size of image is reduced using two-dimensional Discrete wavelet Transform (DWT). then the moment based method is applied on reduced image to determine skew angle. Hence, proposed algorithm has better time complexity and less computational cost than the existing algorithms. this method is tested over large number of documents having skew between -90(square) and +90(square) and is observed to be simple, fast, accurate and works with most of the languages. It is also found to be robust against noise. Results of proposed algorithm are compared with moment based approach and other commonly used existing methods and found to be to the best method.

关键词： Optical character recognition Skew angle Discrete wavelet Transform Moments Time complexity

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Feature Extraction Algorithm based on CSP and wavelet Packet for Motor imagery EEG signals 4

Feature Extraction Algorithm based on CSP and Wavelet Packet...

引用

4th IEEE International conference on signal and image processing (ICSIP)

作者： Feng, Gao LuHao Nuo, Gao Shandong Jianzhu Univ Sch Informat & Elect Engn Jinan 250101 Shandong Peoples R China

ISBN: (纸本)9781728136608

Brain-computer interface (BCI) provides a new way for people who arc unable to communicate with each other. the traditional EEG signal feature extraction method based on frequency characteristics only extracts the energy features of each channel, but ignores the correlation information between different channels. In order to obtain better feature extraction results, the method of EEG signal feature extraction based on wavelet packet and Common Space Pattern (CSP) is adopted in this paper. Firstly, on the basis of analyzing channels and frequency bands closely related to event desynchronization, wavelet packet decomposition was carried out for EEG signals to extract the activity imagination EEG co-rhythms and beta rhythms. Spatial filtering was carried out to extract features through the CSP algorithm, and then the related nodes were selected to calculate the wavelet packet energy. Combining the advantages of wavelet packet and CSP method, the correlation information between different channels can be fully utilized, and the Support Vector Machine (SVM) can be used to classify the two kinds of EEG signals. Corresponding experiments were conducted on BCI competition data sets, the classify results show that the proposed feature extraction algorithm can extract useful features for motor imagery EEG signals and get high classify accuracy.

关键词： component wavelet packet analysis Common space pattern (CSP) Support vector machines (SVM) Brain-computer interface (BCI) Motor imagery (MI) Feature Extraction

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Group-normalized wavelet packet signal processing

Group-normalized wavelet packet signal processing

引用

4th conference on wavelet applications

作者： Shi, Z Bao, Z Xidian Univ. (China)

ISBN: (纸本)0819424935

Since the traditional wavelet and wavelet packet coefficients do not exactly represent the strength of signal components at the very time(space)-frequency tilling, Group-Normalized wavelet Packet Transform (GNWPT), is presented for nonlinear signal filtering and extraction from the clutter or noise, together with the space(time)frequency masking technique. the extended l(p)-entropy improves the performance of GNWPT. For perception based image, soft-logic masking (different from Donoho's method) is emphasized to remove the aliasing with edge preserved. Lawton's method for complex valued wavelets construction is extended to generate the complex valued compactly supported wavelet packets for radar signal extraction. this kind of wavelet packets are symmetry and unitary orthogonal. Well-defined wavelet packets are chosen by the analysis remarks on their time-frequency characteristics. For real valued signal processing, such as images and ECG signal, the compactly supported spline or biorthogonal wavelet packets are preferred for perfect de-noising and filtering qualities.

关键词： group-normalization space(time)-frequency masking soft logic complex wavelet packets

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wavelet analysis of observed geopotential and wind: Blocking and local energy coupling across scales

Wavelet analysis of observed geopotential and wind: Blocking...

引用

4th conference on wavelet applications in signal and image processing

作者： Fournier, A YALE UNIV DEPT PHYSNEW HAVENCT 06520

ISBN: (纸本)0819422134

Atmospheric blocking during three unusual winter months is studied by multiresolution analysis and a wavelet based adaptation of traditional Fourier series based energetics. We demonstrate that blocking, in part a large and localized meteorological phenomenon, is largely described by just the largest scale part of the multiresolution analysis. New forms of the transfer functions of kinetic energy with the mean and eddy parts of the atmospheric circulation are introduced. these quantify the spatially localized conversion of energy between scales. A new accounting method for wavelet indexed transfers permits the introduction of a physically meaningful localized scale flux function. these techniques are applied to the data, and some support is found for the hypothesis that blocking is partially maintained by an inverse cascade.

关键词： atmospheric blocking energetics kinetic energy flux function kinetic energy transfer inverse cascades multiresolution analysis wavelet scale interactions low frequency atmospheric variability

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Efficient, highly scalable wavelet image coding for network applications

Efficient, highly scalable wavelet image coding for network ...

引用

4th International conference on Communications, Circuits and Systems (ICCCAS 2006)

作者： Gan, Tao Zhou, Nan Zhu, Weile UESTC Sch Elect Engn Si Chuan Peoples R China

ISBN: (纸本)0780395840

A new efficient, highly scalable wavelet image coding algorithm is proposed in this paper. Two techniques-morphological representation and quadtree partitioning - are efficiently combined to exploit the nature of wavelet coefficients. thanks to the list structure, the new coding algorithm achieves fine fractional bit-plane coding with negligible additional complexity. Experiments show that it performs comparable or better than the state-of-the-art codecs. Furthermore, the flexible codec supports both quality and resolution scalability, which is very attractive in many network applications.

关键词： image coding Scalability Clustering algorithms Partitioning algorithms Codecs image resolution wavelet coefficients Decoding Gallium nitride IP networks

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A Novel Incremental Face Recognition Method Based on Nonparametric Discriminant Model 4

A Novel Incremental Face Recognition Method Based on Nonpara...

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4th International conference on Advanced Technologies for signal and image processing (ATSIP)

作者： Soula, Arbia Ben Said, Salma Ksantini, Riadh Lachiri, Zied Univ Tunis El Manar Signal Images & Informat Technol LR SITI ENIT Tunis Tunisia Univ Tunis El Manar Signal Images & Informat Technol LR SITI ENIT INSAT Tunis Tunisia Univ Windsor Windsor ON Canada SUPCOM Secur Numer Ariana Tunisia Univ Tunis El Manar ENIT Res Lab SITI Elect Engn Dept Tunis Tunisia

ISBN: (纸本)9781538652398

Face recognition has received considerable interest owing to its relevance in several domains. Yet, it has some difficulties in many real world applications, where data are collected continuously and must be updated over time. In the present, we advance an adept face recognition technique that rests on Incremental Nonparametric Discriminant Analysis (INDA). We use the Gabor wavelet to extract facial features on which multi-lob ordinal filter are applied to derive Ordinal measures that are encoded in local zones, as visual parameters. then, the statistical dispersion of these parameters is integrated to get a feature vector whose dimension is decreased by making use of PCA and variance. Last but not least, every single feature vector is treated as a feature input for the INDA. the proffered face recognition technique was assessed on the well-known ORL and Yale face databases. Experimental results have shown clearly its superiority and skillfulness in terms of recognition performance.

关键词： incremental learning nonparametric discriminant analysis Gabor filter face recognition

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