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

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An adaptive projection algorithm for multirate filter bank optimization

An adaptive projection algorithm for multirate filter bank o...

引用

European signal processing conference (EUSIPCO)

作者： Dong-Yan Huang Phillip A. Regalia Departement Signal & Image Institut National des Telecommunications 9 rue Charles Fourier F-91011 Evry cedex France

We develop a new algorithm for multirate filter bank optimization, which finds application in subband coding or wavelet signal analysis. Although some impressive off-line algorithms have recently been developed for this purpose, the computation demand of such algorithms often renders them prohibitive for real-time applications. In this vein, adaptive filtering solutions remain of interest. A simple gradient descent algorithm may be ill suited due to the nonquadratic nature of the cost function to be minimized, and accordingly non gradient algorithms may offer some attractive alternatives. The present paper describes a projection type algorithm, which aims to construct a lossless filter bank such that one of its impulse responses lies close to an extremal eigenvector of the input signal autocorrelation matrix. Though a formal convergence proof of the algorithm is not offered, simulations show that the algorithm converges to an acceptable vicinity of the global minimum point of the cost function.

关键词： signal processing algorithms Finite impulse response filters Filter banks Cost function Filtering algorithms Algorithm design and analysis Correlation

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Multiresolution autoregressive filtering for pneumonia detection in medical images

Multiresolution autoregressive filtering for pneumonia detec...

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International conference on Digital signal processing (DSP)

作者： I.M. Stephanakis G.K. Anastassopoulos A.D. Tsalkidis National and Technical University of Athens Athens Greece Democritus University of Thrace Alexandroupolis Greece Pediatric Clinic Democritus University of Thrace Alexandroupolis Greece

Digital signal processing provides a variety of algorithmic tools, which are useful in modern medical imaging applications. A novel processing method based upon multiresolution autoregressive filters is proposed for automated detection of child pneumonia in X-ray images. wavelet functions are utilized in order to construct a multiresolution whitening filter which retains information of the texture of the infected lung as well as structural information regarding the relative position of the infected area in the chest. Structural information is incorporated into the autocorrelation function at lower resolution levels whereas texture information is incorporated at finer resolution levels. Combining the outputs of the whitening filters through scales provides for robust and efficient detection of regions with child pneumonia.

关键词： image resolution Filtering Lungs Biomedical imaging signal resolution Filters Digital signal processing signal processing algorithms X-ray detection X-ray detectors

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CHANGE DETECTION ON SAR imageS USING DIVISIVE NORMALIZATION-BASED image REPRESENTATION

CHANGE DETECTION ON SAR IMAGES USING DIVISIVE NORMALIZATION-...

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IEEE International conference on Acoustics, Speech and signal processing

作者： Qian Xu Lina J. Karam School of Electrical Computer and Energy Engineering Arizona State University Tempe AZ

ISBN: (纸本)9781479928941

In the context of multi-temporal synthetic aperture radar (SAR) images for earth monitoring applications, one critical issue is the detection of changes occurring after a natural or anthropic disaster. In this paper, we propose a new similarity measure for automatic change detection based on a divisive normalization image representation. The divisive normalization transform (DNT) has been recognized as a successful methodology to model the perceptual sensitivity of biological vision and a useful image representation that significantly reduces statistical dependence of natural images. In this work, we exploit the fact that the histogram of DNT coefficients within wavelet subbands can often be well fitted with a zero-mean Gaussian density function, which is a one-parameter function that allows efficient change detection of SAR images. The proposed change detector is compared to other recent model-based approaches. Tests on real data show that our detector outperforms previously suggested methods in terms of the rate of false alarm rate and the total error rate.

关键词： images Synthetic aperture radar image representation Rescue Specific absorption rate SAFETY ANALYSIS REPORTS similar measure Dinitrobenzenes one-parameter false alarm probability Error analysis image change detection histograms

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Successive bit-plane rate allocation technique for JPEG2000 image coding

Successive bit-plane rate allocation technique for JPEG2000 ...

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

作者： Y.M. Yeung O.C. An A. Chang Department of Electrical and Electronic Engineering The Hong Kong University of Science and Technology Hong Kong China Hong Kong University of Science and Technology Kowloon HK Dept. of Electr. & Electron. Eng. Hong Kong Univ. of Sci. & Technol. China Department of Electrical and Electronic Engineering The Hong Kong University of Science and Technology

A novel rate control scheme using successive bit-plane rate allocation (SBRA) is proposed for JPEG2000 image coding. By using the current rate-distortion information only, the proposed method can achieve a quality close to the post-compression rate-distortion (PCRD) optimization scheme adopted in JPEG2000. The proposed scheme can efficiently reduce both the computational cost and working memory size of the entropy coding process up to about 90%, in the case of 0.25bpp (1/32) compression. Without using the future rate-distortion information, the sequential property of the proposed method is highly suitable for real-time (or low delay) applications and implementation.

关键词： image coding Rate-distortion Discrete wavelet transforms Bit rate Delay Spatial resolution image resolution Bandwidth image quality Discrete cosine transforms

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A new multifilter design property for multiwavelet image compression

A new multifilter design property for multiwavelet image com...

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

作者： Jo Yew Tham Lixin Shen Seng Luan Lee Hwee Huat Tan Dept. of Math. Nat. Univ. of Singapore Singapore Wavelets Strategic Research Programme Department of Mathematics National University of Singapore Singapore

ISBN: (纸本)0780350413

Approximation order, linear phase symmetry, time-frequency localization, regularity, and stopband attenuation are some criteria that are widely used in wavelet filter design. We propose a new criterion called good multifilter properties (GMPs) for the design and construction of multiwavelet filters targeting image compression applications. We first provide the definition of GMPs, followed by a necessary and sufficient condition for an orthonormal multiwavelet system to have a GMP order of at least 1. We then present an algorithm to construct orthogonal multiwavelets possessing GMPs, starting from any length-2N scalar CQPs. image compression experiments are performed to evaluate the importance of GMPs for image compression, as compared to other common filter design criteria. Our results confirmed that multiwavelets that possess GMPs not only yield superior PSNR performances, but also require much lower computations in their transforms.

关键词： image coding Mathematics Time frequency analysis Streaming media Filter bank Electronic mail Linear approximation Attenuation Nonlinear filters Sufficient conditions

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A GPGPU accelerated compressed sensing with tight wavelet frame transform technique for MR imaging reconstruction

A GPGPU accelerated compressed sensing with tight wavelet fr...

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： B. Hu X. Ma M. Joyce Paul. Glover Buhary. Naleem Department 0 f Engineering Lancaster University Lancaster UK Sir Peter Mansfield Magnetic Resonance Centre University of Nottingham Nottingham UK

High resolution Magnetic Resonance Imaging (MRI) requires long acquisition time to obtain the fully sampled k-space data for image reconstruction. Compressed Sensing (CS) theory has recently been utilized to accelerate the image reconstruction speed by sparsely sampling the k-space. In this work, the CS framework was combined with the Tight wavelet Frame (TWF) transform to further enhance edges/boundaries of MR images and reduce their noise levels. Because the TWF coefficients at finer scale correspond to important image boundary features, the proposed algorithm is able to effectively enhance the signal to noise ratio of MR images without blurring their edges or create artifacts. The resulting constrained minimization problem is then solved iteratively and requires extensive computational resources. To accelerate the reconstruction for real-time medical image processing purpose, the algorithm is implemented on the General Purpose Graphic processing Units (GPGPU). The effects of various factors, including the register counts and block size, on the GPU occupancy have been investigated to tune the hardware for the optimum performance. The proposed algorithm demonstrates great potential to accelerate the MR imaging acquisition by 8-fold without noticeable artifacts. Comparisons with other two l 1 minimization methods with traditional wavelet transforms further confirm the competitiveness of the proposed algorithm. Moreover, a speedup of 45 times was achieved by the GPGPU implementation compared with the CPU version, and therefore making this algorithm suitable for applications in a clinical MRI setting.

关键词： image resolution Acceleration image reconstruction Imaging signal resolution Ear

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A comprehensive approach for texture classification

A comprehensive approach for texture classification

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International Symposium on signal processing and Its applications (ISSPA)

作者： P. Ammi Reddy P. S. R. Chandra Murty E. Sreenivasa Reddy Jawaharlal Nehru Technological University Kakinada A.P. India Department of Computer Science and Engineering Vasireddy Venkatadri Institute of Technology Guntur A.P. India

Classification of textures based on wavelet pattern analysis is one of the most effective methods in texture classification. However using all frequency sub-bands in decomposition for classification may increase time complexity of classification algorithms. To reduce the time complexity, sub-bands with high energy and entropy are selected for classification. Fractal dimension can be used to select such significant sub-bands for decomposition at each level. Further statistical features of these significant sub-bands are given to modified K-NN classifier for classification. This paper describes texture classification using sub-bands of wavelets based on fractal dimensions and their results are compared with the results of texture classification using conventional features and also with different classifiers. Success rate is very high and time complexity is also reduced to the order of O(n).

关键词： Wool Weaving image recognition Computers

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Biometric Cryptosystem Scheme for Internet of Things using Fuzzy Commitment principle

Biometric Cryptosystem Scheme for Internet of Things using F...

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International conference on signal, image, Vision and their applications (SIVA )

作者： Atef Bentahar Abdallah Meraoumia Hakim Bendjenna Salim Chitroub Abdelhakim Zeroual LAboratory of Mathematics Informatics and Systems (LAMIS) University of Larbi Tebessi Tebessa ALGERIA LISIC Laboratory Telecommunication Department USTHB BP. 32 El-Alia Bab-Ezzouar Algiers ALGERIA

ISBN: (纸本)9781538671214;9781538671207

Recently, the ensuring security by biometric authentication/identification presents a big challenge for network designers. This precious biometric information have to be itself protected against fraudulent uses, especially during the remote authentication and data exchange in wireless mesh networks such as the Internet of Things (IoT). This paper presents a securing biometric cryptosystem for IoT based on fuzzy commitment principle which is suitable of the connected things due to their low processing and memorization capacity. Our scheme, which is based on fingerprint modalities, can be decomposed into two parts. Firstly, at the sender side, a biometric feature vector is extracted using DWT technique and then the data is encrypted in order to transmit via internet. Secondly, at the receiver side, an authentication protocol was used to authenticate the things and decrypt the received data. The obtained results, using a popular fingerprint dataset, show that the proposed scheme is more secure, fast and points at increased authentication accuracy.

关键词： Cryptography Fingerprint recognition Authentication Feature extraction Discrete wavelet transforms Internet of Things

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Application of Distributed Arithmetic in image and ECG signal processing

Application of Distributed Arithmetic in Image and ECG Signa...

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International conference on Current Trends in Computer, Electrical, Electronics and Communication

作者： Anu Mary Sunny Naveen Jacob Dept. of Electronics and Communication Engineering Viswajyothi College of Engineering & Technology Vazhakulam Kerala India

ISBN: (纸本)9781538632444

The core of many DSP applications involve convolution which was previously implemented by Multiply and Accumulate operations or MAC. It requires a number of multipliers and accumulators. The use of multipliers and accumulators result in faster execution but it also results in an increase in cost. Also the number of multipliers and adders are limited. Hence a new technique known as Distributed Arithmetic (DA) was proposed. It is basically a multiplier-less concept utilizing Lookup Table (LUT). It is used when one of the operand is fixed. The input enters into a serial register which is used to access the LUT. To get the address from the LUT we consider the bit positions and get the values of inputs by that bit position. The output from the lookup table is shifted accordingly and the shifted results are added together to form the final result. Hence it basically involves accessing the lookup table, shift and add operation. After implementing the DA logic and comparing it with the convolution scheme, we apply this concept in Discrete wavelet Transform (DWT) of an image and ECG signal by using Haar filter coefficient.

关键词： Distributed Arithmetic Discrete wavelet Transform ECG signal

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A DSP for DCT-based and wavelet-based video codecs for consumer applications

A DSP for DCT-based and wavelet-based video codecs for consu...

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Custom Integrated Circuits conference (CICC)

作者： K. Okamoto T. Jinbo T. Araki Y. Iizuka H. Nakajima M. Takahata H. Inoue S. Kurohmaru T. Yonezawa K. Aono Semiconductor Research Center Matsushita Elecrric Indusrrial Company Limited Osaka Japan LSI Development Center Matsushita Electronics Corporation Osaka Japan Corporate Research Division Matsushita Elecrric Indusrrial Company Limited Osaka Japan

We have developed a video DSP which performs real-time encoding and decoding for DCT-based algorithms, such as ITU-T H.261, and wavelet-based subband encoding algorithms. This LSI is suitable for consumer applications as it was implemented using 0.5 /spl mu/m-CMOS process technology to realize compactness (1 million transistors on 65 mm/sup 2/) and low power(560 mW). It features a processing unit which performs wavelet filtering at high speeds, a compact DCT circuit, and a fast, flexible DRAM interface for low-cost systems. At 40 MHz, a single chip is capable of processing QCIF size pictures at a rate of over 15 frames/second.

关键词： Digital signal processing Band pass filters Large scale integration Discrete cosine transforms image coding Convolution Electronics industry Encoding Decoding Application software

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