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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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Surface reconstruction with wavelet transformation 20

Surface reconstruction with Wavelet transformation

引用

20th Jubilee IEEE International conference on Intelligent Engineering Systems (INES)

作者： Balla, Petra Kocsis, Peter Eigner, Gyorgy Antal, Akos BUTE Dept Mechatron Opt & Mech Engn Informat Budapest Hungary Obuda Univ Res & Innovat Ctr Physiol Controls Grp Budapest Hungary

ISBN: (纸本)9781509012169

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： processing

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image Fusion Models and Techniques at pixel level 2

Image Fusion Models and Techniques at pixel level

引用

2nd International conference on image processing, applications and Systems (IPAS)

作者： Ben Salem, Yosra Hamrouni, Kamel Solaiman, Basel Natl Engn Sch Tunis ENIT Signal Image & Informat Proc Lab Tunis Tunisia TELECOM Bretagne Image & Informat Proc Dept Brest France

ISBN: (纸本)9781509016457

Information fusion consists in combining information in order to maximize the relevant information and reduce the redundancy. It is widely used in many fields, especially in image processing, for analyzing situations. Since the first use of the information fusion concept, many approaches have been introduced to define a processing model to merge information. Three basic approaches are used in information fusion: the JDL Model which is the first one used, the Intelligence Cycle Model and the DFD (Data - Features - Decision) Model. According to the field of application and the type of the information manipulated, the processing model is different. In image processing, various techniques and methods are used to perform image fusion. Many techniques are most used in research studies: PCA (Principal Component Analyses), wavelet transform,. In this paper we present a general overview of the basic models and techniques used in image fusion.

关键词： Information Fusion images Fusion JDL Fusion models

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Content Based image Retrieval by Combining Feature Vector

Content Based Image Retrieval by Combining Feature Vector

引用

IEEE International conference on Wireless Communications, signal processing and Networking (WiSPNET)

作者： Ruikar, S. D. Kabade, Rohit S. Walchand Coll Engn Dept Elect Engn Sangli India PVPIT Budhgaon Elect & Comm Engn Dept Sangli India

ISBN: (纸本)9781467393379

This paper describes the searching problem of images stored in big databases i.e. content based image retrieval (CBIR) system. It represents the behaviour and proposes solution for it. In general vast deployment in various applications therefore the capacity of image database increases because it's needed efficient CBIR method. This paper uses the primary image features like colour, shape and texture. This primary features take out using various algorithms those are useful to obtain similarity check into images. It describes the result using MATLAB software application, with a large image database. It utilizes feature of colour, texture and shape of the database images for comparison purpose and further for obtaining of image and it including relevance.

关键词： Color shape texture wavelet etc

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DECONVOLUTION OF POISSONIAN imageS WITH THE PURE-LET APPROACH 23

DECONVOLUTION OF POISSONIAN IMAGES WITH THE PURE-LET APPROAC...

引用

23rd IEEE International conference on image processing (ICIP)

作者： Li, Jizhou Luisier, Florian Blu, Thierry Chinese Univ Hong Kong Dept Elect Engn Hong Kong Hong Kong Peoples R China Roche Diagnost Hematol Boston MA USA

ISBN: (纸本)9781467399616

We propose a non-iterative image deconvolution algorithm for data corrupted by Poisson noise. Many applications involve such a problem, ranging from astronomical to biological imaging. We parametrize the deconvolution process as a linear combination of elementary functions, termed as linear expansion of thresholds (LET). This parametrization is then optimized by minimizing a robust estimate of the mean squared error, the "Poisson unbiased risk estimate (PURE)". Each elementary function consists of a Wiener filtering followed by a pointwise thresholding of undecimated Haar wavelet coefficients. In contrast to existing approaches, the proposed algorithm merely amounts to solving a linear system of equations which has a fast and exact solution. Simulation experiments over various noise levels indicate that the proposed method outperforms current state-of-the-art techniques, in terms of both restoration quality and computational time.

关键词： image deconvolution Poisson noise unbiased risk estimate MSE estimation

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VEHICLE DETECTION IN AERIAL imageS USING MULTISCALE STRUCTURE ENHANCEMENT AND SYMMETRY 23

VEHICLE DETECTION IN AERIAL IMAGES USING MULTISCALE STRUCTUR...

引用

23rd IEEE International conference on image processing (ICIP)

作者： Ram, Sundaresh Rodriguez, Jeffrey J. Univ Arizona Dept Elect & Comp Engn Tucson AZ 85721 USA

ISBN: (纸本)9781467399616

Accurate detection and localization of vehicles in aerial images has a wide range of applications including urban planning, military reconnaissance, visual surveillance, and real-time traffic management. Automated detection of vehicles in aerial imagery is a challenging task, due to the density of vehicles on the road. the complexity of the surrounding environment in urban areas, and low spatial resolution of the image sensor array. We propose an automated method for detecting vehicles of varying sizes in low-resolution aerial imagery. First, we develop a new vehicle enhancement filter involving multiscale Hessian analysis. After thresholding, we refine the candidate vehicle detections based on analysis of bilateral symmetry. We show that our proposed method provides improved detection accuracy compared with existing vehicle detection algorithms for various low-resolution aerial images.

关键词： wavelet transform vehicle detection aerial imagery Hessian filter bilateral symmetry

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Dyadic Lifting wavelet Based signal Detection 3

Dyadic Lifting Wavelet Based Signal Detection

引用

3rd International conference on Artificial Intelligence and Pattern Recognition, AIPR 2016

作者： Kuzume, Koichi Tabusa, Tomonori Department of Information Science Engineering Institute of Technology Yuge College Ehime-ken Japan

ISBN: (纸本)9781467391870

Local regularities of a signal contain important information such as edges in an image and QRS complexes in an Electrocardiogram (ECG). In order to detect such local regularities in the signal, wavelet transform has been focused on as a powerful tool for signal processing applications. wavelet maxima at the time in which the signal abruptly changes are usually large in amplitude. However, with only the magnitude of the wavelet maxima the features of the signal cannot be known in detail. Mallat et al. proposed the Lipchitz regularity for observing signal cross scales in multiresolution signal analysis, but its computational cost was relatively expensive. This paper presents a novel method for signal detection using lifting dyadic wavelet transform, which has the time-invariant property. The lifting wavelet parameters contained in Swelden's formula were tuned, adapting them to the signals to be detected. The method for tuning these parameters was to learn the features of the target signals in the multiresolution analysis. To evaluate our methods we applied them to detect the QRS complexes contained in an ECG. The results showed that our methods were useful to detect target signals accurately. © 2016 IEEE.

关键词： signal detection

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DESIGN OF EFFECTIVE LOW POWER image COMPRESSION ALGORITHM

DESIGN OF EFFECTIVE LOW POWER IMAGE COMPRESSION ALGORITHM

引用

IEEE International conference on Wireless Communications, signal processing and Networking (WiSPNET)

作者： Epshi, G. Saravanan, V. Venkatalakshmi, B. Velammal Engn Coll Madras 600066 Tamil Nadu India

ISBN: (纸本)9781467393379

For satellite communication, large amount of data storage and transmission are involved as the satellites send data all the time, all day. Storing all these data and analyzing them for various purposes is possible using small low cost memory devices only with the help of image compression. image compression is the process of removing the redundant information from the image and it can be stored to reduce the storage size, transmission bandwidth and time. image compression aims at removing duplication from the source image and is essential for applications such as transmission and storage in an efficient form. The objective of the work is to develop an efficient low power image compression algorithm which compress it with higher compression ratio in such a way that the output compressed image becomes compatible for satellite communication. The proposed system should own a light weight algorithm which has the characteristics of minimum power consumption, less compression time and should meet a higher compression ratio. To do image compression, quad tree fractal image compression and an adaptive fractal wavelet image compression algorithm are selected and their performance in terms of mean square error, ratio of compression and peak signal to noise ratio are evaluated.

关键词： Fractal range block image compression quad tree

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Human Age Classification using Facial Skin Analysis and Multi-class Support Vector Machine

Human Age Classification using Facial Skin Analysis and Mult...

引用

International conference on signal and Information processing (IConSIP)

作者： Jagtap, Jayant Kokare, Manesh SGGS Inst Engn & Technol Dept Elect & Telecommun Engn Vishnupuri 431606 Nanded India

ISBN: (纸本)9781509015221

Human age classification via face images becoming an interesting research area because of potential applications in the field of computer vision such as Age Specific Human Computer Interaction (ASHCI), biometrics, security and surveillance, etc. In this paper, a novel method for human age classification using facial skin analysis for aging feature extraction and Multi-class Support Vector Machine (M-SVM) for age classification is proposed to classify the face images into four age groups. Facial skin analysis consists of skin texture analysis and wrinkle analysis. Gabor wavelet is used to analyze the facial skin textural changes with age progression. Wrinkle analysis detects the wrinkle density changes at particular regions on face image with age progression. The performance evaluation of proposed age classification system is carried out by using face images from PAL face database. In this paper, the performance of M-SVM classifier is compared with the performance of Artificial Neural Network ( ANN) classifier for the task of human age classification using Gabor wavelet and wrinkle analysis. The result analysis concludes that the best age classification accuracy of 93.61% is achieved by using proposed age classification system and M-SVM is an efficient classifier than the ANN classifier for the task of human age classification in combination with Gabor wavelet and wrinkle analysis.

关键词： Facial skin analysis Gabor wavelet Wrinkle analysis Multi-class Support Vector Machine (M-SVM) Artificial Neural Network (ANN)

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Data Compression in Wireless Visual Sensor Networks using wavelets

Data Compression in Wireless Visual Sensor Networks using Wa...

引用

IEEE International conference on Wireless Communications, signal processing and Networking (WiSPNET)

作者： Sofi, Shabir Ahmad Naaz, Roohie Natl Inst Technol Srinagar Dept Informat Technol Hazratbal Kashmir India Natl Inst Technol Srinagar Dept Comp Sci & Engn Hazratbal Kashmir India

ISBN: (纸本)9781467393379

Wireless Sensor Networking is a sensor information gathering technology that has a wide range of applications in numerous fields. However due to the fact that sensor nodes have limited battery and are deployed in remote and harsh environments, energy efficient and real time transmission of the information are still open challenges. Since in a wireless sensor network data transmission is the most power consuming task, so far most useful techniques for the purpose of energy efficient and real time transmissions are based on data compression, the majority of them are based on wavelet transform. This paper give performance analysis of different wavelets for energy efficient and real time image data transmission in application like environment monitoring using wireless visual sensor networks. The performance evaluation shows that Haar wavelet is better in terms of energy efficiency and transmission time.

关键词： Wireless Visual Sensor Network (WVSN) Discrete wavelet Transform (DWT) Skipped High-pass Sub-band (SHPS) Data Compression

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Speech signal denoising with wavelet-transforms and the mean opinion score characterizing the filtering quality 13

Speech signal denoising with wavelet-transforms and the mean...

引用

conference on Dynamics and Fluctuations in Biomedical Photonics XIII

作者： Yaseen, Alauldeen S. Pavlov, Alexey N. Hramov, Alexander E. Saratov NG Chernyshevskii State Univ Dept Phys Astrakhanskaya Str 83 Saratov 410012 Russia Univ Technol Baghdad Alsinaa Str Baghdad Iraq Saratov State Tech Univ Res & Educ Ctr Nonlinear Dynam Complex Syst Politech Skaya Str 77 Saratov 410054 Russia Saratov NG Chernyshevskii State Univ Fac Nonlinear Proc Astrakhanskaya Str 83 Saratov 410012 Russia Russian Acad Sci Kotelnikov Inst Radioengn & Elect Saratov Branch Zelyonaya Str 38 Saratov 410019 Russia

ISBN: (纸本)9781628419412

Speech signal processing is widely used to reduce noise impact in acquired data. During the last decades, wavelet-based filtering techniques are often applied in communication systems due to their advantages in signal denoising as compared with the Fourier-based methods. In this study we consider applications of a 1-D double density complex wavelet transform (1D-DDCWT) and compare the results with the standard 1-D discrete wavelet-transform (1D-DWT). The performances of the considered techniques are compared using the mean opinion score (MOS) being the primary metric for the quality of the processed signals. A two-dimensional extension of this approach can be used for effective image denoising.

关键词： wavelet-transform denoising thresholding speech signal

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