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Improving in Spectral Resolution for Closely-Spaced Targets Based on MUSIC Algorithm

Improving in Spectral Resolution for Closely-Spaced Targets ...

引用

International conference on Artificial Intelligence and image processing(ICAIIP’2012);International conference on Innovations in Electrical and Electronics Engineering(ICIEE’2012);International conference on Mechanical,Automobile and Biodiesel Engineering(ICMABE’2012);International conference on History,Literature and Management(ICHLM’2012);International conference on Agriculture,Chemical and Environmental Sciences(ICACES’2012);International conference on Biological and Medical applications(ICBMA’2012)

作者： M.Pourahmadi Department of Electrical Engineering Yazd branchIslamic Azad University

The multiple signal classification (MUSIC) method is severely based on the number of singular values of a multistatic response matrix (or signal subspace rank).In this paper we show that in the presence of multiple scattering between the targets,some singular values will greatly decrease and combine with the noise ones,so the performance of the most popular MUSIC methods degrades and even fails to estimate closely spaced target locations because of a reduction in signal *** such a case,we introduce a method to eliminate ambiguity in determining the number of scatterers employing a pre-processing step by two methods:discrete stationary wavelet transform (DSWT) and empirical mode decomposition (EMD).The DSWT is developed on the basis of features of the reflection coefficient between the *** application of this algorithm to measurement data,shows its superiority over the *** results indicate that MUSIC+DSWT yields accurate estimation of the target locations,even when there exist considerable noise and multiple scattering in the received signal.

关键词： MUSIC algorithm,wavelet transform,spectral resolution,microwave imaging.

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Artificial intelligence for pattern recognition in automated surface engineering

Artificial intelligence for pattern recognition in automated...

引用

International conference on Systems and Informatics (ICSAI)

作者： E. Sheybani S. Garcia-Otero F. Adnani G. Javidi DSP Laboratory Virginia State University Petersburg VA USA

Ability to measure the surface quality in real-time has many applications in manufacturing automation and product optimization, especially in processes in which the surface qualities such as roughness, grain size, thickness of coding, impurities size and distribution, hardness, and other mechanical properties are of importance. Surface analysis in manufacturing environments requires specialized filtering techniques. Due to the immense effect of rough environment and corruptive parameters, it is often impossible to evaluate the quality of a surface that has undergone various grades of processing. The algorithm presented here is capable of performing this comparison analytically and quantitatively at a low computational cost (real-time) and high efficiency. The parameters used for comparison are the degree of blurriness and the amount of various types of noise associated with the surface image. Based on a heuristic analysis of these parameters the algorithm assesses the surface image and quantifies the quality of the image by characterizing important aspects of human visual quality. Extensive effort has been set forth to obtain real-world noise and blur conditions so that the various test cases presented here could justify the validity of this approach well. The tests performed on the database of images produced valid results for the proposed algorithm consistently. This research aims at providing image processing tools for comparison and assessment of a surface processed under different grades of a manufacturing process all the way up to optimal processing. This paper presents the description and validation (along with test results) of the proposed algorithm for surface image quality assessment.

关键词： Surface treatment Noise Algorithm design and analysis Filter banks image quality signal processing algorithms wavelet transforms

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Experimental Investigation for Practical Sparsity Number for image Reconstruction Based on SL0 Algorithm in Discrete Frequency Domain

Experimental Investigation for Practical Sparsity Number for...

引用

International conference on Advanced Information Networking and applications Workshops (AINAW)

作者： Datchakorn Tancharoen Pham Hong Ha Kornkamol Thakulsukanant Vorapoj Patanavijit Faculty of Engineering and Technology Panyapiwat Institute of Management Bangkok Thailand Department of Computer and Network Engineering Faculty of Engineering Assumption University Bangkok Thailand Department of Telecommunications Science Faculty of Science and Technology Assumption University Bangkok Thailand

Compressive Sensing (CS) is known as a new sampling theory that use small number of basis elements for constructing of signals (or images) and these basis elements (so called sparsity number) are very important parameters that approximate how sparsify the image is. Due to several characteristics of each image groups, the sparsity number could be varied and there is unfortunately very little research for this issue. This paper presents two main contributions: First, this paper proposes a practical sparsity number estimation technique using for an image reconstruction for SL0 algorithm based on Discrete Cosine Transform domain (DCT). Second the practical sparsity number of difference image groups is the experiment based on over 2000 images. The DCT is exclusively applied for a sparse representation of images because it is proven as a useful instrument for image analysis and processing. In general, images can be represented by a linear superposition of small number of wavelet elements selected from a suitable filter. The proposed models process the image with Smoothed norm algorithm. This algorithm stated that if signal or image is sufficiently sparse, we can reconstruct it from small amount of none zero basis components. The experiment is comprehensively tested under 2000 sampling images that are categorized in 18 groups by their characteristics. Moreover this sparsity number is practically used for any CS algorithm based on DCT domain.

关键词： PSNR image reconstruction Vectors Discrete cosine transforms Sparse matrices Algorithm design and analysis

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Evaluation of the performance of block matching algorithms in wavelet-based t+2D video coding

Evaluation of the performance of block matching algorithms i...

引用

International conference on Microelectronics, ICM

作者： M. Marzougui A. Zoghlami M. Atri R. Tourki Faculty of Sciences at Monastir Laboratory of Electronic and Microelectronic University of Monastir Monastir Tunisia

Motion estimation is the process of determining the movement of blocks between adjacent video frames by which image information is assessed for similarities that can be reused in subsequent frames. However, computational complexity and resource sharing of the motion estimation algorithm poses great challenges for real time applications. Fast search algorithms emerged as important search technique to achieve real time tracking results. Among the different motion estimation algorithms block matching is the most common used technique. This paper presents a system-level implementation of a wavelet-based t+2D video coding. Three block matching motion estimation algorithms are implemented in order to evaluate the overall system performance. In fact, since the chip design and layout process is time consuming and expensive, it is very important to be able to predict the overall system performance in a highlevel implementation before its circuit layout is deployed. The aim is to discuss the impact of different block matching motion estimation algorithms on video coding performance. Because of the complexity of the entire motion estimation system, decision in choosing one algorithm versus the other algorithms is often empirical and crucial.

关键词： Motion estimation PSNR wavelet transforms signal processing algorithms Cost function Vectors

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Multimodal biometric person recognition system based on fingerprint & Finger-Knuckle-Print using correlation filter classifier

Multimodal biometric person recognition system based on fing...

引用

IEEE International conference on Communications (ICC)

作者： Abdallah Meraoumia Salim Chitroub Ahmed Bouridane Signal and Image Processing Laboratory Electronics and Computer Science Faculty University of Sciences and Technology Houari Boumediene Algiers Algeria Department of Computer Science King Saud University Riyadh Saudi Arabia School of Computing Engineering and Information Sciences Northumbria University Newcastle-upon-Tyne UK

ISBN: (纸本)9781457720529

Biometrics is an effective technology for personnel identity recognition, but uni-modal biometric systems which use a single trait for recognition will suffer from problems like noisy sensor data, non-universality, lack of distinctiveness of the biometric trait, and spoof attacks. These problems can be tackled by using multi-biometrics in the system. Hand-based person recognition provides a reliable, low-cost and user-friendly viable solution for a range of access control applications. As one of the most popular biometric traits, fingerprints (FP) are widely used in personal recognition. However, a novel hand-based biometric feature, Finger-Knuckle-Print (FKP), has attracted an increasing amount of attention. In this paper, FP and FKP are integrated in order to construct an efficient multi-biometric recognition system based on matching score level and image level fusion. In this study we use the minimum average correlation energy (MACE) and Unconstrained MACE (UMACE) filters in conjunction with two correlation plane performance measures, max peak value and peak-to-sidelobe ratio, to determine the effectiveness of this method. The experimental results showed that the designed system achieves an excellent recognition rate on the Hong Kong polytechnic university (PolyU) FKP and high resolution fingerprint database.

关键词： Correlation Databases Training Discrete wavelet transforms Biomedical imaging Biometrics (access control) Fingers

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Application of wavelet transform and image morphology in processing vibration speckle interferogram for automatic analysis

Application of wavelet transform and image morphology in pro...

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conference on Optical Measurement Systems for Industrial Inspection vii

作者： Kumar, Rajesh Jena, Dibya Prakash Shakher, Chandra St Longowal Inst Engn & Technol Dept Mech Engn Precis Metrol Lab Longowal 148106 India Indian Inst Technol Instrument Design Dev Ctr New Delhi 110016 India

ISBN: (纸本)9780819486783

In automatic analysis of the time-average digital speckle interferogram, the great challenge is to get proper intensity variation between different fringes and smoothness in the line profile of intensity distribution, so as it approaches the governing Bessel function/map. An image processing scheme based on wavelet denoising and morphological operation has been investigated which is very effective in reducing speckle index, width reduction of the bright fringes and in getting proper line profile for intensity distribution. Improvement in signal to noise ratio (i.e. decrease in speckle index) upto 28 times has been observed.

关键词： speckle interferogram image processing wavelet morphology speckle index

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ADAPTIVE wavelet image DECOMPOSITION USING LAD CRITERION

ADAPTIVE WAVELET IMAGE DECOMPOSITION USING LAD CRITERION

引用

19th European signal processing conference (EUSIPCO)

作者： Sovic, Ana Sersic, Damir Univ Zagreb Fac Elect Engn & Comp Unska 3 Zagreb 10000 Croatia

In this paper, an adaptive separable 2D wavelet transform is proposed. wavelet transforms are widely used in signal and image processing due to its energy compaction property. Sparser representation corresponds to better performance in compression, denoising, compressive sensing, sparse component analysis and many other applications. The proposed scheme results in more compact representation then fixed wavelet. Instead of the commonly used least squares criterion, least absolute deviation (LAD) is introduced. It results in more accurate adaptation resistant to outliers. The advantages of the proposed method have been shown on synthetic and real-world images.

关键词： Compaction

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The Application of wavelet Analysis in the signal processing

The Application of Wavelet Analysis in the Signal Processing

引用

International conference on Graphic and image processing (ICGIP)

作者： Li Ruibin Cui Baozhen TaiYuan Univ Technol YangQuan Coll Yangquan Peoples R China North Univ China Sch Mech Engn & Automat Taiyuan Peoples R China

ISBN: (纸本)9780819489326

This paper introduces applications of wavelet analysis in mechanical signal processing based on the therory wavelet analysis and wavelet recognition. It can effectively distinguish different running states of rolling bearing through picking up character of scale-energy. It is one of the important characteristics of signal singularity and irregular mutation that it includes important information. Analysis singularity and the site of singularity using wavelet transform is more effective because wavelet transform has space localization property. In wavelet analysis, the low frequency part of signal represents the development trend of the signal. It corresponds to the maximum scale wavelet coefficients. With the increase of scale, the resolution of time, the development trend of the signal can be more apparent, so wavelet analysis on display the development trend of signal is very useful. Along with the computer hardware technology and specially the DSP technology development, it will provide powerful safeguard for wavelet analysis using project.

关键词： wavelet analysis wavelet recognition signal processing

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A DSP Implementation of Lifting Based DWT for image processing applications

A DSP Implementation of Lifting Based DWT for Image Processi...

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International conference on Graphic and image processing (ICGIP)

作者： Gholipour, Morteza Noubari, Hossein Ahmadi Kamarei, Mahmoud Univ Tehran ECE Dept Tehran Iran Univ British Columbia Vancouver BC Canada

ISBN: (纸本)9780819489326

Discrete wavelet Transform (DWT) is widely used in signal processing applications. In this paper, we describe hardware implementation of a lifting-based DWT, which is used in image compression. The CDF(2,2) lifting-based wavelet transform is modeled and simulated using MATLAB. Based on DSP methodologies, the signal flow graph and dependence graph are derived. The dependence graph is optimized and used to implement the hardware description of the circuit in Verilog. We have synthesized and implemented the circuit using both Field Programmable Gate Array (FPGA) and Application Specific Integrated Circuit (ASIC) design approaches. To confirm the circuit operation, post-synthesis and post-layout simulations were done for FPGA and ASIC designs, respectively.

关键词： DWT Lifting wavelet DSP VLSI implementation

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wavelet Analysis and High Quality JPEG2000 Compression Using Daubechies wavelet

Wavelet Analysis and High Quality JPEG2000 Compression Using...

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International conference on Graphic and image processing (ICGIP)

作者： Khalid, Azra Afsheen, Uzma Baig, Saad Umer Nokia Siemens Networks Karachi Pakistan NED Univ Engn & Technol Dept Elect Engn Karachi Pakistan

ISBN: (纸本)9780819489326

wavelet analysis and its application has found much attention in recent times. It is vastly applied in many applications such as involving transient signal analysis, image processing, signal processing and data compression. It has gained popularity because of its multiresolution, subband coding and feature extraction features. The paper describes efficient application of wavelet analysis for image compression, exploring Daubechies wavelet as the basis function. wavelets have scaling properties. They are localized in time and frequency. wavelets separate the image into different scales on the basis of frequency content. The resulting compressed image can then be easily stored or transmitted saving crucial communication bandwidth. wavelet analysis because of its high quality compression is one of the feature blocks in the new JPEG2000 image compression standard. The paper proposes Daubechies wavelet analysis, quantization and Huffman encoding scheme which results in high compression and good quality reconstruction.

关键词： wavelet analysis image compression JPEG2000 Huffman encoding discrete wavelet transform multiresolution analysis quantization

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