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检索条件"任意字段=2nd Conference on Image Reconstruction from Incomplete Data"

共 4214 条记录，以下是101-110 订阅

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image reconstruction using Orthogonal Matching Pursuit (OMP) Algorithm 2

Image Reconstruction using Orthogonal Matching Pursuit (OMP)...

引用

2nd IEEE International conference on Emerging Technology Trends in Electronics, Communication and Networking (ET2ECN)

作者： Goklani, Hemant S. Sarvaiya, Jignesh N. Fahad, A. M. SVNIT ECED Dept Surat 392001 Gujarat India

ISBN: (纸本)9781479969869

According to Shannon-Nyquist sampling criteria for reconstruction of information from the received signal, sampling rate must be twice or higher than signal bandwidth. But in many signal and image processing applications, due to this higher Nyquist rate too many samples are produced and compression becomes prior requirement for storage or transmission for this huge amount of data. The recent theory of Compressed Sensing is utilized to capture and represent compressible signals at a far lowest rate than the Nyquist rate. So signals can be reconstructed from critically undersampled measurements by taking advantage of their inherent low-dimensional structure. In this paper, one of the compressed sensing algorithm, namely Orthogonal Matching Pursuit (OMP) is applied to the domain of image reconstruction and its performance is evaluated at different sparsity levels and the stability of algorithms is studied in the presence of noise.

关键词： Compressed sensing OMP Nyquist rate Sampling

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Anchor neighborhood embedding based single-image super-resolution reconstruction with similarity threshold adjustment 2021

Anchor neighborhood embedding based single-image super-resol...

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2nd International conference on Artificial Intelligence and Information Systems (ICAIIS )

作者： Xiong, Min Song, Yun Xiang, Yongshen Xie, Bin Deng, Zhelin Changsha Univ Sci & Technol Hunan Prov Key Lab Intelligent Proc Big Data Tran Changsha 410114 Peoples R China Changsha Univ Sci & Technol Sch Comp & Commun Engn Changsha 410000 Hunan Peoples R China Hunan Prov Transportat Planning Survey & Amp Desi Changsha 410008 Peoples R China

ISBN: (纸本)9781450390200

Anchored neighborhood super-resolution (SR) reconstruction algorithms reconstruct a high-resolution (HR) image from a single low resolution (LR) image effectively by exploiting the non-local similarity in images. In this paper, we propose an anchored neighborhood reconstruction algorithm with a similarity threshold adaptive scheme to improve the reconstruction for the mapping matrix. In the proposed method, a similarity adjustment matrix is introduced to improve the similarity of the image blocks with high deviation in the neighborhood. Besides, a threshold function is applied to determine the weights for similar blocks. Following this function, larger weights are assigned to samples with low deviations and low coefficients are assigned to blocks with low similarity. This scheme is employed to prevent the blocks from being assigned inappropriate weights and benefit the reconstruction. Experimental results show that the proposed algorithm improves the image reconstruction quality with a low computational cost.

关键词： Anchored neighborhood embedding Super-resolution Block similarity Mapping matrix

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Comparison of 1-minimization and iteratively reweighted least squares-p-minimization for image reconstruction from compressive sensing

Comparison of 1-minimization and iteratively reweighted leas...

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2010 2nd International conference on Advances in Computing, Control and Telecommunication Technologies, ACT 2010

作者： Endra, Oey Gunawan, Dadang Department of Electrical Engineering Universitas Indonesia Depok 16424 Indonesia

ISBN: (纸本)9780769542690

Compressive sensing is the recent technique in data acquisition that allows to reconstruct signal form far fewer samples than conventional method i.e. Shannon-Nyquist theorem use. In this paper, we compare 1- minimization and Iteratively Reweighted Least Squares (IRLS)-p- minimization algorithm to reconstruct image from compressive measurement. Compressive measurement is done by using random Gaussian matrix to encode the image that the first be divided into number of blocks to reduce to the computational complexity. from the results, IRLS-p and 1-minimization provided almost the same image reconstruction quality, but the IRLS-p-minimization resulted the faster computation than 1-minimization algorithm. © 2010 IEEE.

关键词： Compressed sensing

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Repairing incomplete measured data with haptic interaction

Repairing incomplete measured data with haptic interaction

引用

2009 2nd International Congress on image and Signal Processing, CISP'09

作者： Siyuan, Cheng Siquan, Liang Xiangwei, Zhang Faculty of Electromechanical Engineering Guangdong University of Technology Guangzhou China

ISBN: (纸本)9781424441310

Measured data of a product can be incomplete because of the inaccessibility or invisibility of some portions of the product surface for measure tools in reverse engineering, which could makes it difficult for reverse engineering systems to create the CAD model from those measured data. In this paper, a novel incomplete data repair method based on haptic interaction is presented. Starting from the import of a dataset digitized from a physical object, various haptic sculpting tools are explored to repair the incomplete measured data, and the shape and size of these tools may be changed dynamically to satisfy specific situations, which forms a flexible and intuitive sculpting toolbox used to clean and repair the measured data. A high-quality STL file can be obtained from the system which is ideal for rapid prototyping. Case study is also given to demonstrate the feasibility of this new method, and finally a future direction of integration repairing measured data with designing innovative new object through haptic interaction in reverse engineering is proposed. ©2009 IEEE.

关键词： Reverse engineering

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An Improved Fast Fractal image Coding Algorithm

An Improved Fast Fractal Image Coding Algorithm

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2nd International conference on Computer Science and Network Technology (ICCSNT)

作者： Tang Guowei Wu Shuang Zhang Yan Northeast Petr Univ Sch Comp & Informat Technol Daqing Heilongjiang Peoples R China

ISBN: (纸本)9781467329644;9781467329637

With the development of the Internet, new requirements are put forward on image compression effect, compression ratio and encoding and decoding time. The principle of fractal coding is novel. It breaks through the traditional entropy boundary theory. Especially its high compression ratio makes the fractal image coding become a hot research point. But this method has the encoding and decoding lopsided problem. Based on the basic principle of fractal image compression, this paper proposes a calculation method which is based on the main diagonal, namely only using the two diagonal data to do mean calculation. Thus not only reduce the data in operation, but also make the time be reduced to a certain degree. The experimental results show that, under the same quality of the image reconstruction, the algorithm makes the encoding and decoding time be greatly reduced

关键词： Fractal Theory image Compression Fractal image Coding Iterative Function System

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Can broad-band image restoration rival speckle restoration?

Can broad-band image restoration rival speckle restoration?

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2nd conference on image reconstruction from incomplete data

作者： Fraser, D Lambert, A Jahromi, MRS Clyde, D Donaldson, N Univ New S Wales Univ Coll Sch Elect Engn Canberra ACT 2600 Australia

ISBN: (纸本)0819445592

The restoration of images formed through atmospheric turbulence is usually attempted through operating on a sequence of speckle images. The reason is that high spatial frequencies in each speckle image are effectively retained though reduced in magnitude and distorted in phase. However, speckle imaging requires that the light is quasi-monochromatic. An alternative possibility, discussed here, is to capture a sequence of images through a broadband filter, correct for any local warping due to position-dependent tip-tilt effects, and average over a large number of images. In this preliminary investigation, we simulate several optical transfer functions to compare the signal levels in each case. The investigation followed encouraging results that we obtained recently using a blind-deconvolution approach. The advantages of such a method are that narrow-band filtering is not required, simplifying the equipment and allowing more photons for each short exposure image, while the method lends itself to restoration over fields of view wider than the isoplanatic patch without the need to mosaic. The preliminary conclusions are that, so long as the ratio of the telescope objective diameter, D, to Fried parameter, r(0), is less than about 5, the method may be a simple alternative to speckle imaging.

关键词： digital image restoration speckle restoration blind deconvolution astronomical imaging surveillance imaging atmospheric turbulence optical flow image registration

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Adaptive Recovery of incomplete datasets for Edge Analytics 2

Adaptive Recovery of Incomplete Datasets for Edge Analytics

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2nd IEEE International conference on Fog and Edge Computing (ICFEC)

作者： Lujic, Ivan De Maio, Vincenzo Brandic, Ivona Vienna Univ Technol Inst Informat Syst Engn Favoritenstr 9-11-194 A-1040 Vienna Austria

ISBN: (纸本)9781538664889

The Internet of Things (IoT) has attracted significant attention from both academia and industry, thanks to applications such as smart cities, smart buildings and intelligent traffic management. These systems rely on data, collected from IoT devices, that are sent to the cloud for analytics. data are either used for near real-time decisions or stored for long-term analysis. However, in highly distributed IoT systems, missing or invalid data may appear because of different reasons including sensor failures, monitoring system failures and network failures. Analyzing incomplete datasets can lead to inaccurate results and imprecise decisions, with negative effects on the target systems. Also, due to the increasing size of such systems and the consequently increasing amount of data generated from sensors, recovery of incomplete datasets for analytics on the cloud is often infeasible, due to the limited bandwidth available and the strict latency constraints of IoT applications. We propose a novel semi-automatic recursive mechanism for recovery of incomplete datasets on the edge that is closer to the source of data. This mechanism enables efficient recovery of incomplete datasets employing different forecasting techniques for multiple gaps, based on user specifications. We evaluate our approach on datasets coming from the context of smart buildings and smart homes. The experimental results show that our approach is able to identify multiple gaps, then recover incomplete datasets, decreasing forecasting error by up to 82.68%, and reducing running time by up to 52.38%.

关键词： Edge Computing Internet of Things time series incomplete data data recovery forecasting techniques

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A novel DFT/RDFT based subband representation for the fusion of remote sensing images

A novel DFT/RDFT based subband representation for the fusion...

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2nd International conference on Recent Advances in Space Technologies

作者： Sezgin, M Erer, I Ersoy, OK Tech Univ Istanbul Inst Informat TR-34469 Istanbul Turkey

ISBN: (纸本)0780389778

We present a new fusion algorithm using a novel multidecomposition approach based on a DFT/RDFT-based symmetric, zero-phase, nonoverlapping digital filter bank representation. For the panchromatic image and each band of the multispectral image, the lowpass and highpass subband components are obtained in a tree structure using zero-phase filters implemented by the RDFT. The approximation subband of the multispectral image is merged with the detail subbands of the panchromatic image. The fused data is recovered from the subband signals by a new perfect reconstruction algorithm. This process is performed on each band of the multispectral image to obtain the final fused high resolution multispectral image.

关键词： image fusion

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A Chaos-Based image Encryption Algorithm Using Wavelet Transform

A Chaos-Based Image Encryption Algorithm Using Wavelet Trans...

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2nd IEEE International conference on Advanced Computer Control

作者： Zhu Yu Zhou Zhe Yang Haibing Pan Wenjie Zhang Yunpeng Northwestern Polytech Univ Coll Software & Microelect Xian 710072 Peoples R China

ISBN: (纸本)9781424458479

In recent years many chaos-based image cryptosystems are proposed. As encryption process is applied to the whole image, it is difficult to improve the efficiency. In this paper, wavelet decomposition is used in our algorithm to concentrate the main information of image to the low frequency part. Then high-strength chaotic encryption is applied. After that, wavelet reconstruction and Arnold scrambling are used for diffusion. Finally, another wavelet decomposition and encryption round is needed to complete the encryption. The effective acceleration of chaos-based image cryptosystem is thus achieved. Theoretical analysis and experimental results show that the proposed algorithm has large key-space, high efficiency, and satisfied security, suits for image data transmission.

关键词： cryptography wavelet transform chaos

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Compressive Sensing approach for data Recovery from incomplete Measurements for One dimensional Signal 2

Compressive Sensing approach for Data Recovery from Incomple...

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2nd International conference on Applied and Theoretical Computing and Communication Technology (iCATccT)

作者： Parate, Pratik Kanjalkar, Pramod Vishwakarma Inst Technol Instrumentat Engn Dept Pune Maharashtra India KL Univ Dept ECE Guntur India

ISBN: (纸本)9781509023998

In various situations there is a need to measure and transmit fast moving data such as in Radar, Oceanography, Continuous Monitoring of Meteorological Parameters, etc. It may sometimes happen that some data gets lost. So to recover this information complete original data is to be resent. In this paper, we have discussed a new type of signal acquisition theory called as Compressive Sensing (CS). Signals having Sparse representation in one or the other domain can be faithfully reconstructed from the random undersampled measurements. Naturally occurring signals such as audio signals are having sparse nature in Fourier Domain. One such implementation of CS theory is also explained and demonstrated. Greedy Algorithm known as Orthogonal Matching Pursuit is used in recovery process.

关键词： Compressive Sensing (CS) Sparsity RIP OMP

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