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检索条件"主题词=Compression algorithms"

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An ECG Data compression Method via Standard Deviation and ASCII Character Encoding

An ECG Data Compression Method via Standard Deviation and AS...

引用

International Conference on Emerging Applications of Information Technology (EAIT)

作者： S.K. Mukhopadhyay M. Mitra S. Mitra Department of Applied Physics University of Calcutta Kolkata India Department of Electronics Netaji Nagar Day College University of Calcutta Kolkata India

In the present paper, a software based effective ECG data compression algorithm is proposed. The whole algorithm is written in C- platform. The algorithm is tested on various ECG data of all the 12 leads taken from PTB Diagnostic ECG Database (PTB-DB). In this compression methodology, individual standard deviation of each part of the signal is calculated at first. To achieve a strict loss less compression in regions of high standard deviation and a tolerable lossy compression in rest of the signal, two different compression algorithms have developed. It is observed that this proposed algorithm can reduce the file size significantly. The data reconstruction algorithm has also been developed using the reversed logic and it is seen that data is reconstructed preserving the significant ECG signal morphology.

关键词： Arrays Electrocardiography Encoding Data compression compression algorithms Decoding Wavelet transforms

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Lossless compression of Hyperspectral Image Based on 3DLMS Prediction

Lossless Compression of Hyperspectral Image Based on 3DLMS P...

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Congress on Image and Signal Processing, CISP

作者： Yonghong Chen Zelin Shi Deqiang Li Chinese Academy of Sciences Beijing Beijing CN Shenyang Institute of Automation Chinese Academy and Sciences Shenyang China

This aiming at improving the lossless compression ratio of hyperspectral image, a three-dimensional LMS (3DLMS) algorithm is first deduced and applied into the field of hyperspectral image compression. A novel adaptive prediction model based on 3DLMS algorithm for lossless compression of hyperspectral image is proposed and optimized by the local casual set mean subtraction method. Experimental results on AVIRIS images show that the proposed algorithm can remove both the spatial and spectral redundancy of hyperspectral image and achieve higher image compression ratios than other state-of-the-art compression algorithms. The feasibility of 3DLMS algorithm in three-dimensional signal processing is also verified in this paper.

关键词： Image coding Hyperspectral imaging Signal processing algorithms Hyperspectral sensors Least squares approximation Predictive models compression algorithms Adaptive filters Adaptive signal processing Accuracy

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Connectivity-Guided Predictive compression of Dynamic 3D Meshes

Connectivity-Guided Predictive Compression of Dynamic 3D Mes...

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IEEE International Conference on Image Processing

作者： Nikolce Stefanoski Jorn Ostermann Institut für Informationsverarbeitung Universität Hannover Hanover Germany

We introduce an efficient algorithm for real-time compression of temporally consistent dynamic 3D meshes. The algorithm uses mesh connectivity to determine the order of compression of vertex locations within a frame. compression is performed in a frame to frame fashion using only the last decoded frame and the partly decoded current frame for prediction. Following the predictive coding paradigm, local temporal and local spatial dependencies between vertex locations are exploited. In this framework we present a novel angle preserving predictor and evaluate its performance against other state of the art predictors. It is shown that the proposed algorithm improves up to 25% upon the current state of the art for compression of temporally consistent dynamic 3D meshes.

关键词： Coherence Predictive coding Decoding Animation Principal component analysis Wavelet transforms compression algorithms Quantization Prediction methods Linear predictive coding

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Impact of vector quantization compression on hyperspectral data in the retrieval accuracies of crop chlorophyll content for precision agriculture

Impact of vector quantization compression on hyperspectral d...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Baoxin Hu Shen-en Qian D. Haboudane J.R. Miller A. Hollinger N. Tremblay Canadian Space Agency QUE Canada Department of Physics and Astronomy York University Toronto ONT Canada Center for Research in Earth and Space Science York University Toronto ONT Canada Agriculture and Agi-Food Canada Research Branch Horticulture Research and Development Center Saint Jean sur Richelieu QUE Canada

In this study, impacts of vector quantization compression on prediction of leaf chlorophyll content of crops for the application to precision agriculture were evaluated. The compression algorithm tested in this paper is called successive approximation multi-stage vector quantization (SAMVQ). The hyperspectral data used were acquired by CASI over corn fields at L' Acadie experimental farm (Agriculture and Agri-Food Canada) during the summer of 2000. Nine zones in the corn fields with different fertilization levels (no fertilization, intermediate fertilization, and over-fertilization) were used to evaluate the difference between the leaf chlorophyll contents obtained from original and reconstructed reflectance data cubes. The root mean square errors (RMSEs) and the correlations between the chlorophyll content derived from the original data cube and that derived from the reconstructed data cubes were calculated in the nine zones. The spatial variability of chlorophyll content in the nine zones was also examined for the images of chlorophyll content created from the original and reconstructed reflectance data cubes. The results show that the chlorophyll content image created from the reconstructed reflectance data cube corresponding to SAMVQ with a compression ratio of 20 maintains good agreement with that derived from the original reflectance data cube in the nine zones in terms of estimated pigment mean and spatial variability. As a result, SAMVQ with a compression ratio of 20 is considered acceptable for the retrieval of crop chlorophyll content from CASI hyperspectral data for agriculture corn crops.

关键词： Vector quantization Hyperspectral imaging Information retrieval Content based retrieval Crops Agriculture Image reconstruction Reflectivity Image coding compression algorithms

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Implementation of Template Matching Based ECG compression Algorithm for Mobile Application

Implementation of Template Matching Based ECG Compression Al...

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International Conference on IT Convergence and Security (ICITCS)

作者： Byeong-Hoon Kim Yun-Hong Noh Do-Un Jeong Dept. of Ubiquitous IT Engineering Dongseo University Busan South Korea Division of Computer & Information Engineering Dongseo University Busan South Korea

In this paper, a template based ECG compression algorithm for mobile device application is proposed and *** threshold is applied for good R-peak detection *** for PQ interval, QRS complex, ST interval is *** template code that closely matched with the input signal is saved. The determining factor for "closely matched" is based on the calculation of MSE value after comparing the template with each of the intervals (PQ interval, QRS complex and ST interval) with real time input ECG *** performance of algorithm is evaluated by using the Massachusetts Institute of Technology-Boston's Beth Israel Hospital Normal Sinus Rhythm Database and different sampling record. The highest compression ratio is 15.2:1. The accuracy of the R-peak detection is 100%.

关键词： Electrocardiography compression algorithms Real-time systems Monitoring Mobile communication Rhythm Databases

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Adaptive Header compression Algorithm in Narrow Band Internet of Things

Adaptive Header Compression Algorithm in Narrow Band Interne...

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IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Hao Liu Chenhong Zhou Tieyi Yang College of Microelectronics Southeast University Wuxi China

ISBN: (数字)9781728180281

ISBN: (纸本)9781728180298

As an Internet of Things (IOT) network to realize the Internet of Everything, Narrowband Internet of Things (NB-IoT) is widely applied in large-scale small data services, such as meter reading and streetlamp control. Currently, NB-IoT protocols are carried by complete IP, realize network transmission by using the TCP/UDP transport protocols, and implement header compression through robust header compression (ROHC). The two-way reliable R, two-way optimization O, and one-way U modes of the ROHC algorithm have the drawbacks of a high feedback cost, dependence of the feedback effect on the network quality, and desynchronization of decompressor. Therefore, an optimized Markov chain prediction model was added to the U mode of ROHC, and an adaptive header compression algorithm (ROHC-M), which could adjust the state of compression according to the channel conditions, was developed. Compared with the one-way mode algorithm, the proposed ROHC-M algorithm decreased the header size by 0.96 bytes on average and increased the throughput by 10%.

关键词： Predictive models Markov processes Prediction algorithms Internet of Things IP networks compression algorithms Narrowband

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A two dimensional wavelet packet approach for ECG compression

A two dimensional wavelet packet approach for ECG compressio...

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International Symposium on Signal Processing and Its Applications (ISSPA)

作者： A.R.A. Moghaddam K. Nayebi Signal Computing Limited Iran Sharif University of Technology Iran

An improved compression algorithm for ECG signals is presented using temporal alignment of beats and 2-D wavelet packet transform (WPT). This 2-D transform based approach utilizes the fact that the electrocardiogram (ECG) signals generally show two types of correlation, namely correlation between subsequent samples within each ECG cycle (intrabeat) and correlation between subsequent cycles (interbeat). One simple compression algorithm in the 2-D WPT domain, which is applied to some records in the MIT-BIH arrhythmia database shows lower percent root mean square difference (PRD) than 1-D wavelet based compression methods for the same compression ratio (CR).

关键词： Wavelet packets Electrocardiography Discrete wavelet transforms Wavelet transforms Signal analysis Entropy compression algorithms Wavelet domain Time frequency analysis Fourier transforms

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Level-embedded lossless image compression

Level-embedded lossless image compression

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： M. Celik A.M. Tekalp G. Sharma Department of Electrical and Computer Eng. University of Rochester Rochester NY USA Xerox Corporation Webster NY USA

A level-embedded lossless compression method for continuous-tone still images is presented. Level (bit-plane) scalability is achieved by separating the image into two layers before compression and excellent compression performance is obtained by exploiting both spatial and inter-level correlations. A comparison of the proposed scheme with a number of scalable and non-scalable lossless image compression algorithms is performed to benchmark its performance. The results indicate that the level-embedded compression incurs only a small penalty in compression efficiency.

关键词： Image coding Scalability Streaming media Transform coding Image reconstruction Law Legal factors compression algorithms Pixel Image resolution

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On implementing a client-server setting to prevent the Browser Reconnaissance and Exfiltration via Adaptive compression of Hypertext (BREACH) attacks

On implementing a client-server setting to prevent the Brows...

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Manufacturing & Industrial Engineering Symposium (MIES)

作者： Isuru Sankalpa Tharindu Dhanushka Nadeesha Amarasinghe Janaka Alawathugoda Roshan Ragel Department of Computer Engineering University of Peradeniya Peradeniya Sri Lanka

ISBN: (纸本)9781509036301

compression is desirable for network applications as it saves bandwidth. Differently, when data is compressed before being encrypted, the amount of compression leaks information about the amount of redundancy in the plaintext. This side channel has led to the “Browser Reconnaissance and Exfiltration via Adaptive compression of Hypertext (BREACH)” attack on web traffic protected by the TLS protocol. The general guidance to prevent this attack is to disable HTTP compression, preserving confidentiality but sacrificing bandwidth. As a more sophisticated countermeasure, fixed-dictionary compression was introduced in 2015 enabling compression while protecting high-value secrets, such as cookies, from attacks. The fixed-dictionary compression method is a cryptographically sound countermeasure against the BREACH attack, since it is proven secure in a suitable security model. In this project, we integrate the fixed-dictionary compression method as a countermeasure for BREACH attack, for real-world client-server setting. Further, we measure the performance of the fixed-dictionary compression algorithm against the DEFLATE compression algorithm. The results evident that, it is possible to save some amount of bandwidth, with reasonable compression/decompression time compared to DEFLATE operations. The countermeasure is easy to implement and deploy, hence, this would be a possible direction to mitigate the BREACH attack efficiently, rather than stripping off the HTTP compression entirely.

关键词： Dictionaries Servers compression algorithms Cryptography Browsers Encoding Bandwidth

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Research on image compression algorithm based on Rectangle Segmentation and storage with sparse matrix

Research on image compression algorithm based on Rectangle S...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Shengli Chen Xiaoxin Cheng Jiapin Xu School of Electronics and Information Engineering Sichuan University Chengdu Sichuan China

The Quarter-tree decomposition of image compression method characters with relative simplicity and fast calculation, however compression ratio is not very high. In order to overcome this flaw, one new segmentation method named the Rectangle Segmentation is proposed, in which adjacent pixel points satisfying consistency condition are viewed as the same image block. Also, without the restriction of square which abides to 2 n , the image block can be rectangle which reduces the amount of block, and improves the compression ratio. Image compression ratio can be further augmented by combining the storage method of sparse matrix. Therefore, a new image compression algorithm is proposed named the Rectangle Segmentation and Sparse Matrix Storage(RSSMS) compression algorithm. Simulation results indicate that the compression ratios of images using the new algorithm is 25.19% higher than those using the Quarter-tree decomposition method.

关键词： Image coding Image segmentation Sparse matrices Image reconstruction compression algorithms PSNR Gray-scale

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