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International conference on Wireless Communications, signal processing and Networking

作者： S. D. Ruikar Rohit S. Kabade Electronics Engg Dept. Walchand College of Engineering Sangli India Electronics & Comm. Engg Dept PVPIT Budhgaon Sangli India

ISBN: (纸本)9781467393393

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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Data Compression in Wireless Visual Sensor Networks using wavelets

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

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International conference on Wireless Communications, signal processing and Networking

作者： Shabir Ahmad Sofi Roohie Naaz Department of Information Technology National Institute of Technology Srinagar Hazratbal Kashmir India Department of Computer Science & Engineering National Institute of Technology Srinagar Hazratbal Kashmir India

ISBN: (纸本)9781467393393

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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Digital watermarking scheme for image authentication

Digital watermarking scheme for image authentication

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International conference on Communication and signal processing

作者： Lakshmi Priya, C. V. Nelwin Raj, N. R. SreeChitraThirunal College of Engineering Thiruvananthapuram India

Digital image watermarking process is definite as to insert information of digital into digital signal. This is an efficient solution to avoid illegal copying of information from multimedia networks. Many watermarking algorithms have been developed and each of them has its own individuality because of its variety of applications. A new algorithm able to solve most of the practical issues of watermarking is designed. Watermarking alone is not sufficient to prevent the unauthorized manipulations of data unless a proper protection protocol is established. An efficient watermarking algorithm should satisfy an optimal trade-off between three factors such the capacity, robustness and imperceptibility. The proposed algorithm uses the advantage of singular value decomposition (SVD), discrete wavelet transform (DWT) and homomorphic filtering. Finally, the efficiency of the result is evaluated using various quality measurements and the watermarked image is encrypted to increase the security level.

关键词： Digital water marking DWT SVD Homomorphic filtering Encryption

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DESIGN OF EFFECTIVE LOW POWER image COMPRESSION ALGORITHM

DESIGN OF EFFECTIVE LOW POWER IMAGE COMPRESSION ALGORITHM

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International conference on Wireless Communications, signal processing and Networking

作者： G. Epshi V. Saravanan B. Venkatalakshmi Velammal Engineering College Chennai- 600066 India

ISBN: (纸本)9781467393393

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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Glaucomatous image Classification using wavelet Transform

Glaucomatous Image Classification using Wavelet Transform

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International conference on Advanced Communication Control and Computing Technologies

作者： A.Rajan G.P.Ramesh J.Yuvaraj Department of ECE St. Peter's UniversityChennai India Department of ECE St. Peter's UniversityChennai India Shri Andal Alagar College of Engineering Mamandur India.

ISBN: (纸本)9781479939152

wavelet Transforms is a part of large community of mathematical function approximation method, they are being increasing and being deployed in image processing for segmentation, filtering, classification etc. This work is based on image classification with the use of single level Discrete wavelet Transform (DWT). wavelets have been employed in many applications of signal *** texture features within images are extracted for accurate and efficient Glaucoma Classification. Energy is distributed over the wavelet sub-bands to find these important texture features. The discriminatory potential of wavelet features obtained from the daubechies (db3), symlets (sym3), and reverse biorthogonal (rbio3.3, rbio3.5, and rbio3.7) wavelet filters. We propose a technique to extract energy features obtained using 2-D discrete wavelet transform. The energy features obtained from the detailed coefficients can be used to distinguish between normal and glaucomatous images with very high accuracy. The effectiveness is evaluated using K- NN classifier by taking 30 normal and glaucoma images, 15 images are used for training and 15 images for testing.

关键词： Biomedical optical imaging feature extraction glaucoma image texture wavelet transforms

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Research on Three Typical Methods of Infrared Weak Small Targets Background Suppression under Cloud Background

Research on Three Typical Methods of Infrared Weak Small Tar...

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2015 International conference on Materials Engineering and Information Technology applications(MEITA 2015)

作者： Zhongmin LI Guowei ZOU Lifei MEI School of Information Engineering Nanchang Hangkong University

ISBN: (纸本)9781510812055

Background suppression of weak small targets in infrared image is the key of image tracking and monitoring, especially under the cloud background. In the area of image signal processing, there are a lot of background suppression methods can be used to image filter by combining the characteristics of infrared image under the cloud background. In this paper, we introduce three typical background filter methods such as pulse median filter, multi-structural morphological filter and wavelet threshold method, realize them using MATLAB, and analyze their performances of background suppression of weak small targets in infrared image under the cloud background.

关键词： Background Suppression Infrared image Cloud Background

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Pipeline and Parallel Processor Architecture for Fast Computation of 3D-DWT using Modified Lifting Scheme

Pipeline and Parallel Processor Architecture for Fast Comput...

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International conference on Wireless Communications, signal processing and Networking

作者： C. Ashok Kumar B. K. Madhavi K. Lalkishore Department of ECE CMR Engineering College Department of ECE Sridevi Women Engineering College Department of ECE JNTU Anantapur

ISBN: (纸本)9781467393393

A pipelined parallel processing 3D DWT architecture is designed in this paper based on lifting scheme algorithm with 9/7 wavelet filters. The 3D DWT architecture process a 512×512 image with 8 groups of frames sequentially with improved throughput. The first stage computes 1D-DWT along the rows with 4 parallel processors, the memory interface with FIFO reduces latency between first stage and second stage that computes 2D DWT computation. 3D DWT computes wavelet coefficients in the temporal direction and designed to operate from 512*4 clock cycles in sequence along with 1D and 2D DWT computation. The FIFO designed synchronizes the data movement. Memories at every stage are designed to store the parallel processed data. The proposed architecture has high performance and is suitable for high speed, low power and portable applications. With utilization of 51% of slice registers 3D-DWT architecture implemented on Virtex-5 FPGA and frequency of operation is 373 MHz. The designed DWT-IDWT can be used as IP Core.

关键词： Lifting scheme Pipelined architecture 3D DWT Parallel processing FPGAs

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A time-scale based objective function for EEG signal parameters optimization

A time-scale based objective function for EEG signal paramet...

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International conference on Electrical Engineering

作者： Asma Bouchema Abdellah Kacha Antoine Nonclercq Francis Grenez Laboratory of Physics of Radiation and Applications Department of Automatic Jijel University Laboratories of Image Signal processing and Acoustics Universite Libre de Bruxelles

ISBN: (纸本)9781467366748

This paper concerns the optimization of EEG signal parameters for epileptic seizure detection. In a previous study, a macroscopic model has been used to model various waveforms of EEG signal and to optimize its parameters by means of a genetic algorithm (GA). In the GA-based method for EEG parameters estimation, an optimization procedure is used. The aim of the optimization procedure is to minimize an objective function. The minimized error function compares the desired waveform (real EEG signal) and the waveform of the signal provided by the model both in the time domain and frequency domain. In the present study, we propose a time-scale based representation for the objective function as an alternative to the time and frequency based objective function used in the early study. The proposed objective function takes into account the non-stationary nature of the EEG signal. The performance of the proposed wavelet-based objective function is compared to that of the spectral objective function.

关键词： Epileptic seizure detection Objective function EEG parameters optimization Time-scale analysis

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Double Density Dual Tree Discrete wavelet Transform implementation for Degraded image Enhancement

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Journal of Physics: conference Series 2018年第1期1000卷

作者： C Vimala P Aruna Priya Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur India

wavelet transform is a main tool for image processing applications in modern existence. A Double Density Dual Tree Discrete wavelet Transform is used and investigated for image denoising. images are considered for the analysis and the performance is compared with discrete wavelet transform and the Double Density DWT. Peak signal to Noise Ratio values and Root Means Square error are calculated in all the three wavelet techniques for denoised images and the performance has evaluated. The proposed techniques give the better performance when comparing other two wavelet techniques.

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The role of the coarsest resolution subband in the wavelet-based reconstruction of signals from gradients

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Journal of Physics: conference Series 2017年第1期933卷

作者： Ioana S. Sevcenco Panajotis Agathoklis Electrical and Computer Engineering Department University of Victoria Canada

An efficient wavelet-based algorithm to reconstruct non-square/non-cubic signals from gradient data is proposed. This algorithm is motivated by applications such as image or video processing in the gradient domain. In some earlier approaches, the non-square/non-cubic gradients were extended to enable a square/cubic Haar wavelet decomposition and the coarsest resolution subband was derived from the mean value of the signal. In this paper, a non-square/non-cubic wavelet decomposition is obtained directly without extending the gradient data. The challenge comes from finding the coarsest resolution subband of the wavelet decomposition and an algorithm to compute this is proposed. The performance of the algorithm is evaluated in terms of accuracy and computation time, and is shown to outperform the considered earlier approaches in a number of cases. Further, a closer look on the role of the coarsest resolution subband coefficients reveals a trade-off between errors in reconstruction and visual quality which has interesting implications in image and video processing applications.

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