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检索条件"主题词=Compression algorithm"

共 134 条记录，以下是61-70 订阅

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Piecewise compression of large mesh

Piecewise compression of large mesh

引用

Conference on Vision Geometry XIV

作者： Qin, Aihong Xiong, Hua Shi, Jiaoying Liu, Zhen Zhejiang Univ CAD&CG State Key Lab Hangzhou 310027 Peoples R China Shanxi Univ Sch Comp & Informat Technol Taiyuan 030006 Peoples R China

ISBN: (纸本)0819461067

Large and detailed 3D polygon mesh with standard representation results in files of gigantic size. The need for more compact representations and a parallel implementation is clear. But the compressed gigantic mesh applied in parallel rendering to achieve high performance is still an unexplored area. In this work, we present a mesh compression scheme employed in parallel rendering system. It includes two parts: Mesh segmentation and segments compression. Firstly, the multilevel graph partitioning idea is adopted to separate the mesh into large patches with less curvature. Then the large patches are farther partitioned with MeTiS[1] to get small patches with a balanced vertex counts. As the multilevel mesh produced by the feature preserved mesh simplification procedure, our segmentation algorithm takes both the segment's flatness and balanced vertex counts into account. Secondly, each patch is compressed separately. The vertices in the patch are classified into two distinguish types, namely boundary vertex and inner vertex, different compression algorithm are applied to them. The boundary vertexes are compressed with a novel compression algorithm PMC proposed in this work. To avoid decoding the whole boundary during every frame rendering, the boundary vertexes are compressed piecewise. The successive boundary edges shared by the same patches can act as a piece element when it is compressed. During sorting only the encoded boundary in the view-frustum needs to be loaded and decompressed. Experiments show that the encoded mesh can be partitioned in compression-domain in parallel rendering system. It reduces the communication bandwidth requirement significantly.

关键词： mesh compression compression algorithm parallel rendering mesh segmentation large mesh coding sorting triangle mesh simplification feature preserved

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Polynomial Based Representation for DNA Sequence compression and Search 3

Polynomial Based Representation for DNA Sequence Compression...

引用

3rd IEEE-Pune-Section International Conference (PuneCon)

作者： Khan, Waqar Ahmad Khan, Aftab Univ Engn & Technol UET Dept Comp Syst Engn Peshawar 25120 Pakistan

ISBN: (纸本)9781728196008

Data compression plays an important role in lesser expensive resource consumption. It is also cumbersome to send a huge amount of data through the network. The data compression techniques help in optimizing physical storage devices as well as it makes easy to transfer the compressed data or file faster through internet or network. Deoxyribonucleic acid or DNA is biological traits presents in human and almost all other living organisms. The DNA contains the genetic information of the living organisms. In this research, various compression algorithms for DNA sequences are studied and compared. The scheme proposed here for compression is the use of a burrows wheeler compression technique. Our proposed algorithm is the modification of the Burrows Wheeler compression algorithm (BWCA). The lexicographical sorting of the matrix is replaced by the polynomial base representation of the bases of DNA. This method reduces the time for compression positively. Validation was performed on various datasets that concur the efficiency of the proposed scheme.

关键词： compression Ratio compression algorithm DNA Data compression

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REST: A Reference-based Framework for Spatio-temporal Trajectory compression 18

REST: A Reference-based Framework for Spatio-temporal Trajec...

引用

24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

作者： Zhao, Yan Shang, Shuo Wang, Yu Zheng, Bolong Quoc Viet Hung Nguyen Zheng, Kai Soochow Univ Inst Artificial Intelligence Suzhou Peoples R China Soochow Univ Sch Comp Sci & Technol Suzhou Peoples R China King Abdullah Univ Sci & Technol Thuwal Saudi Arabia Chinese Univ Hong Kong Hong Kong Peoples R China Huazhong Univ Sci & Technol Wuhan Hubei Peoples R China Aalborg Univ Aalborg Denmark Griffith Univ Brisbane Qld Australia Univ Elect Sci & Technol China Chengdu Sichuan Peoples R China

ISBN: (纸本)9781450355520

The pervasiveness of GPS-enabled devices and wireless communication technologies results in massive trajectory data, incurring expensive cost for storage, transmission, and query processing. To relieve this problem, in this paper we propose a novel framework for compressing trajectory data, REST (Reference-based Spatio-temporal trajectory compression), by which a raw trajectory is represented by concatenation of a series of historical (sub-)trajectories (called reference trajectories) that form the compressed trajectory within a given spatio-temporal deviation threshold. In order to construct a reference trajectory set that can most benefit the subsequent compression, we propose three kinds of techniques to select reference trajectories wisely from a large dataset such that the resulting reference set is more compact yet covering most footprints of trajectories in the area of interest. To address the computational issue caused by the large number of combinations of reference trajectories that may exist for resembling a given trajectory, we propose efficient greedy algorithms that run in the blink of an eye and dynamic programming algorithms that can achieve the optimal compression ratio. Compared to existing work on trajectory compression, our framework has few assumptions about data such as moving within a road network or moving with constant direction and speed, and better compression performance with fairly small spatio-temporal loss. Extensive experiments on a real taxi trajectory dataset demonstrate the superiority of our framework over existing representative approaches in terms of both compression ratio and efficiency.

关键词： compression algorithm trajectory spatio-temporal data

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Sensor Data Stream On-line compression with Linearity-based Methods 6

Sensor Data Stream On-line Compression with Linearity-based ...

引用

6th IEEE International Conference on Smart Computing (SMARTCOMP)

作者： Vaananen, Olli Hamalainen, Timo JAMK Univ Appl Sci Sch Technol Jyvaskyla Finland Univ Jyvaskyla Fac Informat Technol Jyvaskyla Finland

ISBN: (纸本)9781728169972

The escalation of the Internet of Things applications has put on display the different sensor data processing methods. The sensor data compression is one of the fundamental methods to reduce the amount of data needed to transmit from the sensor node which is often battery powered and operates wirelessly. Reducing the amount of data in wireless transmission is an effective way to reduce overall energy consumption in wireless sensor nodes. The methods presented and tested are suitable for constrained sensor nodes with limited computational power and limited energy resources. The methods presented are compared with each other using compression ratio and inherent latency. Latency is an important parameter in on-line applications. The improved variation of the linear regression-based method called RT-LRbTC is tested and it has proved to be a potential method to be used in a wireless sensor node with a fixed and predictable latency. The compression efficiency of the compression algorithms is tested with real measurement data sets.

关键词： edge computing internet of things sensor data compression algorithm

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Segmentation of Measurement Data for Improvement of compression Efficiency

Segmentation of Measurement Data for Improvement of Compress...

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International Siberian Conference on Control and Communications (SIBCON)

作者： Un, Chye En Fedyaev, Alexandr U. Levenets, Alexey V. Pacific Natl Univ Dept Automat & Syst Engn Khabarovsk Russia

ISBN: (纸本)9781479971039

In the paper, the method of data preprocessing by segmentation procedure needed for increasing efficiency of compressing is offered. The basic principle of segmentation procedure of input data sequence is described and the data compression algorithm is offered. The efficiency of proposed method as data compression procedure and also as data preprocessing procedure before using of some compression algorithm is shown.

关键词： compression algorithm data preprocessing information and measurement system measurement data

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compression and Indexing Based on BWT: A Survey

Compression and Indexing Based on BWT: A Survey

引用

10th Web Information System and Application Conference (WISA)

作者： Zhang, Dengfeng Liu, Qing Wu, Yuewan Li, Yaping Xiao, Lin Renmin Univ China Sch Informat Beijing Peoples R China

ISBN: (纸本)9780769551340

Burrows-Wheeler Transform (BWT) is a new data transform method, firstly introduced by Burrows and Wheeler in 1994 and used in a lossless data compression algorithm. In the original version of data compression algorithm based on BWT, Burrows and Wheeler used the Move-To-Front (MTF) transform after the BWT and entropy coding (Huffman coding) for encoding the transform result in the last stage. Ferragina and Manzini combined the compression algorithm based on BWT and the suffix array data structure, and proposed a new opportunistic data structure. They shortly called it FM-index in that it is a Full-text index and occupies Minute space. This paper mainly describes the methods about compression and index based on BWT, and relationship between them. At last, the paper compares some tools.

关键词： BWT compression algorithm full-text indexes FM-index

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compression Methods for Microclimate Data Based on Linear Approximation of Sensor Data 19th

Compression Methods for Microclimate Data Based on Linear Ap...

引用

19th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems (NEW2AN) / 12th Conference on the Internet of Things and Smart Spaces ruSMART (Are You Smart)

作者： Vaananen, Olli Hamalainen, Timo JAMK Univ Appl Sci Ind Engn Sch Technol Jyvaskyla Finland Univ Jyvaskyla Fac Informat Technol Jyvaskyla Finland

ISBN: (纸本)9783030308599;9783030308582

Edge computing is currently one of the main research topics in the field of Internet of Things. Edge computing requires lightweight and computationally simple algorithms for sensor data analytics. Sensing edge devices are often battery powered and have a wireless connection. In designing edge devices the energy efficiency needs to be taken into account. Pre-processing the data locally in the edge device reduces the amount of data and thus decreases the energy consumption of wireless data transmission. Sensor data compression algorithms presented in this paper are mainly based on data linearity. Microclimate data is near linear in short time window and thus simple linear approximation based compression algorithms can achieve rather good compression ratios with low computational complexity. Using these kind of simple compression algorithms can significantly improve the battery and thus the edge device lifetime. In this paper linear approximation based compression algorithms are tested to compress microclimate data.

关键词： Edge computing Internet of Things compression algorithm

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Saliency Prediction using Scene Motion for JND based Video compression

Saliency Prediction using Scene Motion for JND based Video C...

引用

IEEE Workshop on Signal Processing Systems (SiPS)

作者： Wang, Ruei-Jiun Chiu, Ching-Te Natl Tsing Hua Univ Dept Comp Sci Hsinchu 30043 Taiwan

ISBN: (纸本)9781457719219

Due to the popularity of online repositories, an efficient compression algorithm that removes statistical redundancy and psychovisual redundancies without perceptual degradation is important for data transmission and storage. Visual attention model and visual sensitivity model are proposed for removing psychovisual redundancies. However most visual attention models are based on spatial component analysis, and only a few adopt motion vectors for temporal component analysis, which lacks perceptual information. This paper proposes a scene motion and saliency motion based visual attention model that effectively traces the movement of salient regions, and incorporates the obtained motion saliency map with Just Noticeable Distortion (JND) to determine the quantization parameters. The proposed framework achieves an 8% to 73% bit rate reduction compared with the H. 264 in version JM14.0, and its bit rate reduction is three times higher than the previous methods. Visual quality assessment experiments indicate that participants cannot distinguish the difference between the compressed video streams and the original video streams.

关键词： Adaptation models Bit rate Humans Image coding JND based video compression Quantization Sensitivity Visualization compressed video stream compression algorithm data compression data storage data transmission image motion analysis just noticeable distortio

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Still image compression analysis

Still image compression analysis

引用

46th International Symposium Electronics in Marine (ELMAR -2004)

作者： Novosel, D Kovac, M RIZ Transmitters Ltd Zagreb Croatia

ISBN: (纸本)9537044025

JPEG2000 is the latest ISO/IEC standard for still image coding. Its core part has already been published as an international standard (IS), and work on its subsequent parts is under way. In this paper author's encoder implementation compliant with core part of JPEG2000 will be presented, as well as results of comparison between presented JPEG2000 encoder implementation and two publicly available JPEG and JPEG-LS implementations. Also, main features of JPEG2000 standard in comparison to somewhat older JPEG and JPEG-LS international standards will be briefly described.

关键词： still image compression JPEG JPEG-LS JPEG2000 compression algorithm comparison subjective quality testing

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Comparative Study between Various algorithms of Image compression Techniques using MODIS Image 4

Comparative Study between Various Algorithms of Image Compre...

引用

4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Gadallah, Omkulthoum G. Nasr, Mohamed E. Elkhobby, Heba Ali Banha University Faculty of Engineering Electronics and Electrical Communications Engineering Department Egypt Tanta University Faculty of Engineering Electronics and Electrical Communications Engineering Department Egypt

ISBN: (纸本)9798350343670

compression techniques have a vital role to minimize the cost of information storage and/or transmission. In particular, techniques of image compression make the use of visual perception and statistical properties of image information to provide superior performance in comparison with the other conventional compression techniques. However, high-resolution images may face many compression challenges, especially when hiding them as embedding stage information. In this paper, the performance of four different compression techniques was evaluated and compared. These four different compression techniques are Discrete Cosine Transform 'DCT', Singular Value Decomposition (SVD), Block Truncation Coding (BTC), and Gaussian pyramid (GP) bench-mark techniques. Comparison results between objects composed of high- and medium-resolution imaging spectroradiometer (MODIS) images are presented, using signal-to-noise ratio (PSNR), correlation (CORR), mean square error (MSE), and structural similarity index (SSIM) as metrics to perform the test, it was found that BTC has the best performance in image recovery compared to other comparative techniques. © 2024 IEEE.

关键词： BTC compression algorithm DCT GP MODIS and Aerosols Stago information SVD

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