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检索条件"任意字段=Conference on Wavelet Applications in Signal and Image Processing VII"

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A coarse-grained reconfigurable wavelet denoiser exploiting the Multi-Dataflow Composer tool

A coarse-grained reconfigurable wavelet denoiser exploiting ...

引用

conference on Design and Architectures for signal and image processing

作者： Nicola Carta Carlo Sau Francesca Palumbo Danilo Pani Luigi Raffo Universita degli Studi di Cagliari Cagliari Sardegna IT

In the last few years, efficient resource management turned out to be one of the major challenges for hardware designers. Strategies of reusability through reconfiguration have demonstrated interesting potentials to address it, providing also power and area minimization. The Multi-Dataflow Composer (MDC) tool has been presented to the scientific community to automatically build-up runtime coarse-grained reconfigurable platforms. Originally conceived in the field of Reconfigurable Video Coding (RVC), the MDC allows achieving attractive results also for hardware designers operating in different application fields. In this work, we intend to demonstrate the potential orthogonality of the MDC approach with respect to the RVC domain. A runtime reconfigurable wavelet denoiser, targeted for biomedical applications, has been developed and prototyped onto an FPGA Development Board Spartan 3E 1600. Impressive results in terms of resource minimization have been achieved with respect to more traditional solutions.

关键词： Kernel Noise reduction Coprocessors Hardware Approximation methods Runtime Libraries

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Surface reconstruction with wavelet transformation

Surface reconstruction with Wavelet transformation

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IEEE International conference on Intelligent Engineering Systems (INES)

作者： Petra Balla Peter Kocsis György Eigner Ákos Antal Department of Mechatronics Optics and Mechanical Engineering Informatics BUTE Budapest Hungary Research and Innovation Center of Obuda University Obuda University Budapest Hungary

The development in computing power highlights some forgotten algorithms, which were neglected because of their complexity and slowness on early computers. One example is the wavelet-Transformation Profilometry (WTP) of which successful application is demonstrated in the paper. WTP is a high level signal processing method using orthogonal algorithms for huge datasets. The high performance in quality and running speed makes the described method suitable for medical image processing applications.

关键词： wavelet transforms Surface waves Surface treatment Surface reconstruction image reconstruction Computers

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Kinship Verification Using Multiscale Retinex Preprocessing and Integrated 2DSWT-CNN Features

Kinship Verification Using Multiscale Retinex Preprocessing ...

引用

International conference on image and signal processing and their applications (ISPA)

作者： El Ouanas Belabbaci Mohammed Khammari Ammar Chouchane Abdelmalik Ouamane Mohcene Bessaoudi LIMED Laboratory Faculty of Technology University of Bejaia Bejaia Algeria LIMED Laboratory Faculty of Exact Sciences University of Bejaia Bejaia Algeria Faculty of Sciences and Technology University Center of Barika Barika Algeria Laboratory of LI3C University Mohamed Khider of Biskra Biskra Algeria

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

Kinship verification from facial images presents a challenging yet intriguing problem within the fields of pattern recognition and computer vision. In this study, we introduce significant advancements by applying a preprocessing technique known as Multiscale Retinex with Color Restoration (MSRCR) to enhance the quality and contrast of images. Our methodology uniquely combines the strengths of both deep and shallow feature descriptors by integrating them at the score level through the use of Logistic Regression (LR). Specifically, we utilize a novel descriptor, Histograms of a Two-Dimensional Stationary wavelet Transform (Hist-2D-SWT), to capture non-deep features, while employing the CNN model for deep feature extraction. The efficacy of our approach is thoroughly evaluated through extensive experiments conducted on three challenging kinship datasets: Cornell KinFace, UB KinFace, and TS KinFace.

关键词： wavelet transforms Logistic regression Histograms Computer vision image color analysis signal processing Feature extraction

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Lattice structure for two-channel filter banks with complex coefficients, which yield symmetric wavelet bases

Lattice structure for two-channel filter banks with complex ...

引用

European signal processing conference (EUSIPCO)

作者： Todor Cooklev Akinori Nishihara Masaki Kato Dept. Electr. & Comp. Eng. University of Toronto 10 King's College Rd. Toronto ON M5S 1A4 Canada Dept. Physical Electronics Tokyo Inst. Technology 2-12-1 Ookayama Meguro-ku Tokyo 152 Japan

A new lattice structure is described. It is capable of implementing all paraunitary two-channel filter banks where the filters have complex coefficients and yield symmetric wavelet bases. This lattice structure, while being a general design method, can also be used to actually design the filter bank. These filter banks are, in fact, a special case of multifilter banks and can also be related to Golay-Rudin-Shapiro complementary polynomial pairs. The applications of such filter banks are to be found in subband coding and communications systems.

关键词： Lattices Polynomials wavelet transforms image reconstruction Filter banks Design methodology

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Pulp Fibre Recognition Based on Curvelet Transform and Skeleton Tracing Algorithm

Pulp Fibre Recognition Based on Curvelet Transform and Skele...

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IEEE conference on Industrial Electronics and applications (ICIEA)

作者： Jianmei Bian Shubo Qiu Automation Lab Shandong Institute of Light Industry Jinan Shandong China

In the analysis of pulp fibre, the characteristics of pulp fibre are important parameters in papermaking industry. In this paper, the curvelet transform and skeleton tracing method based on preferential direction were introduced to analyze the paper pulp fibre images. The curvelet transform was developed based on the Fourier transform, wavelet transform and radon transform. It has overcome some limitations of wavelet in representing orientations of edges in images. The theory and implementation of curvelet transform were summarized. In this paper, the curvelet transform was used to analyze the pulp fibre images, and the different characteristics of each fibre were extracted to disjoin the intersect fibres; the crossed or furcated fibres were distinguished by the width information. Experiment results showed that the proposed algorithm obtained perfect effects in the analysis of pulp fibre images.

关键词： Skeleton Optical fiber theory image edge detection Fourier transforms wavelet transforms image analysis Algorithm design and analysis signal processing wavelet analysis Character recognition

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Perceptual-Shaping Comparison of DWT-Based Pixel-Wise Masking Model with DCT-Based Watson Model

Perceptual-Shaping Comparison of DWT-Based Pixel-Wise Maskin...

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IEEE International conference on image processing

作者： Gui Xie M.N.S Swamy M. Omair Ahmad Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

It is very important to perceptually shape the watermark signal before embedding it into a host image according to the characteristics of the HVS (human vision system) since watermark invisibility is a necessary requirement for a successful watermarking application. Two popular HVS models have been proposed to deal with this problem: DCT-based Watson model and DWT-based PWM (pixel-wise masking) model, which correspond to the DCT-based and DWT-based watermarking techniques, respectively. Even though there is a common belief that the PWM model is better than the Watson model, there have been no studies that compare these two approaches. This paper is devoted to such a comparison. Our results show that the believed superiority of the PWM model relative to the Watson model is not correct and the Watson model indeed outperforms the PWM model. We argue that more accurate masking strategies in the wavelet domain are needed for DWT-based watermarking applications.

关键词： Discrete wavelet transforms Watermarking Pulse width modulation Discrete cosine transforms Spread spectrum communication Pixel image quality Robustness Humans wavelet domain

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image super resolution scheme based on wavelet transform and its performance analysis

Image super resolution scheme based on wavelet transform and...

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International conference on Computing, Communication & Automation (ICCCA)

作者： P. B. Chopade P. M. Patil Sinhgad College of Engineering Pune India KJ's Educational Institute Pune India

ISBN: (纸本)9781479988914

Super resolution is very useful and interesting area of research in image processing applications based on wavelet transform. Many algorithms have been developed by researchers based on Projection Onto Convex Set (POCS), Maximum-aposteriori (MAP) and Maximum Likelihood (ML). In this paper, we propose super resolution algorithm based on Stationary wavelet Transform (SWT) and Discrete wavelet Transform (DWT). Single frame super resolution can be achieved by use of different interpolation method but this scheme generates blur at the edges of images. Hence in this paper we relied on wavelet transform for super resolution algorithm with different orthogonal and bi-orthogonal filters. Quality aspect of image such as MSE, PSNR, SSIM and Correlation Coefficient are calculated with this proposed algorithm.

关键词： Discrete wavelet transforms Spatial resolution Interpolation signal resolution

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USING image Features to Identify Camera Sources

USING Image Features to Identify Camera Sources

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Min-Jen Tsai Guan-Hui Wu Institute of Information Management National Chiao Tung University China

Digital forensics has lately become one of the very important applications to identify the characteristics and the originality of the digital devices. This study has focused on analyzing the relationship between digital cameras and the associated images. Digital image processing technology has been applied with data mining method to get images' features. Those features were trained and classified to identify the camera sources from the images. In addition, the identification features were further categorized for improvements, based on the analyses, to enhance the precision rate of the identification. This research also compared not only cameras of different brands, but also those of the same manufacturer with similar models. This research has found that the feature based approach has better performance to distinguish the camera sources among brands. Further findings are discussed and suggested for the potential limit of the identification methods in real applications

关键词： Digital images Digital cameras Pixel Color image quality wavelet domain Information management Digital forensics image analysis Data mining

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image retrieval for compressed and uncompressed images

Image retrieval for compressed and uncompressed images

引用

International conference on Information, Communications and signal processing

作者： Vidya R. Khapli Anjali S Bhalchandra K K Wagh Womens Polytechnic Nashik India Government College of Engineering Aurangabad India

ISBN: (纸本)9781424446568

To reduce the storage and transmission requirements in image applications, images are compressed while maintaining acceptable visual quality. In this paper, image retrieval using Vector Quantization (VQ) is explored. The VQ technique is tested on uncompressed images (UCID) as well as compressed images (JPG). In order to reduce the retrieval time, the images are converted into thumbnails and the retrieval performance in both the domains is observed. The testing is performed with various thumbnail sizes. Performance is evaluated by using Precision and Recall. It is observed that the retrieval performance using VQ for compressed images remains comparable with that with uncompressed images.

关键词： image retrieval image coding image storage Indexing Information retrieval Pixel Vector quantization Discrete Fourier transforms Discrete wavelet transforms Testing

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SAR image denoising: a multiscale robust statistical approach

SAR image denoising: a multiscale robust statistical approac...

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International conference on Digital signal processing (DSP)

作者： A. Achim A. Bezerianos P. Tsakalides Department of Medical Physics University of Patras Greece Institute for Space Applications & Remote Sensing National Observatory of Athens Greece

Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of the scattering phenomenon. It appears sensible to reduce speckle in SAR images, provided that the structural features and textural information are not lost. We present a novel speckle removal algorithm within the framework of wavelet analysis. First, we show that the subband decompositions of logarithmically transformed SAR images are best described by alpha-stable distributions, a family of heavy-tailed densities. Consequently, we design a maximum a posteriori (MAP) estimator that exploits this a priori information. We use the alpha-stable model to develop a blind speckle-suppression processor that performs a non-linear operation on the data, and we relate this non-linearity to the degree of non-Gaussianity of the data. Finally, we compare our proposed method to a current state-of-the-art soft thresholding technique applied on an aerial image and we quantify the achieved performance improvement.

关键词： image denoising Robustness Speckle Ultrasonic imaging Noise shaping Statistical distributions Biomedical imaging Filtering wavelet transforms wavelet coefficients

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