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检索条件"主题词=compression algorithms"

共 2082 条记录，以下是461-470 订阅

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Adaptive lossless forward move dictionary based compression

Adaptive lossless forward move dictionary based compression

引用

International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Deepa Raj Seema Gupta BabaSaheb Bhimrao Ambedkar University Lucknow INDIA

ISBN: (纸本)9781479968329

For storing and transmitting data from one end to another, size of the data should be reduced in size for better bandwidth and increase speed of device. Online compression is in great demand as more and more of the work is on online platform. Numerous static compression methods are there but they are time consuming and require complete data before compression. It requires two pass compressions but online compression take one pass compression for encoding and decoding simultaneously. A dictionary based compression technique can be applied to reduce the data size for better bandwidth utilization and hence faster transmission of data. In this paper we generate dictionary of incoming data according to first come first serve basis. Initially first block of some size is compressed using adaptive tree method and simultaneously dictionary is generated during processing and a particular code of 9 bits is provided for each string generated with LZW method and forward move basis method. The efficiency will be enhanced if repetition of string is greater in the document. We use a median to store coming data during transmission of previous data after compression. This way we create a block of data of particular size and apply compression on the block.

关键词： Dictionaries Image coding Vegetation Adaptation models Receivers Bandwidth compression algorithms

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A multi-phase approach to floating-point compression

A multi-phase approach to floating-point compression

引用

IEEE International Conference on Electro-Information Technology

作者： Kevin R. Townsend Joseph Zambreno Department of Electrical and Computer Engineering Iowa State University Ames IA USA

This paper presents a lossless double-precision floating point compression algorithm. Floating point compression can reduce the cost of storing and transmitting large amounts of data associated with big data problems. A previous algorithm called FPC performs well and uses predictors. However, predictors have limitations. Our program (fzip) overcomes some of these limitations, fzip has 2 phases, first BWT compression, second value and prefix compression with variable length arithmetic encoding. This approach has the advantage that the phases work together and each phase compresses a different type of pattern. On average, fzip achieves a 20% higher compression ratio than other algorithms.

关键词： Arrays Plasmas Encoding Transforms Computers compression algorithms Big data

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Irreversible wavelet compression of radiological images based on visual threshold

Irreversible wavelet compression of radiological images base...

引用

IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)

作者： B. K. Chandrika P. Aparna S. Sumam David Department of Electrical & Electronics Engineering Manipal Institute of Technology Manipal University Manipal India Department of Electronics & Communication Engineering National Institute of Technology Karnataka Surathkal India National Institute of Technology Karnataka Surathkal Karnataka IN

ISBN: (纸本)9781467387856

Visually lossless irreversible coding permit compression algorithms to improve the compression gain without disturbing the visual image quality. This paper proposes a novel coding scheme in which wavelet based visual model is embedded into lossless compression algorithm to compress the volumetric medical image data. Obtained experimental results are compared with numerically lossless compression schemes such as Differential Pulse Code Modulation (DPCM), Joint Photographic Experts Group-Lossless (JPEG-LS), JPEG-2000 and High Efficiency Video Coding (HEVC). The proposed method achieves reduced bit rate without deteriorating the visual quality of the resulting images.

关键词： Image coding Discrete wavelet transforms Visualization Magnetic resonance imaging Biomedical imaging Computed tomography compression algorithms

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compression and data mining

Compression and data mining

引用

International Conference on Computing, Networking and Communications (ICNC)

作者： Dan A. Simovici Tong Wang Ping Chen Dan Pletea Univ. of Massachusetts Boston Boston USA

Data compression plays an important role in data mining in assessing the minability of data and a modality of evaluating similarities between complex objects. We focus on compressibility of strings of symbols and on using compression in computing similarity in text corpora; also we propose a novel approach for assessing the quality of text summarization.

关键词： Data mining Abstracts Vectors compression algorithms Sorting Correlation Vocabulary

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A scheme of structured data compression and query on Hadoop platform

A scheme of structured data compression and query on Hadoop ...

引用

International Conference on Digital Information, Networking, and Wireless Communications (DINWC)

作者： Xiangwu Ding Bo Tian Yefeng Li Department of Computer Science and Technology University of Donghua Shanghai China

ISBN: (纸本)9781479963775

We proposed a scheme of data compression and query technology to improve the performance of processing structured data on Hadoop platform. Firstly, we designed a data page structure for row-column hybrid storage based on HDFS. Then we proposed and implemented an adaptive lightweight data compression strategy based on MapReduce to compress and store data as the proposed storage structure. Finally, we provided a query strategy which directly execute on the compressed data of the given storage structure. The experiments conducted on the large-scale datasets demonstrated the effectiveness of the proposed strategy on reducing the amount of storage and improving query performance for structured data.

关键词： Data compression Encoding Query processing compression algorithms Big data Data analysis Dictionaries

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Fast LZW compression Using a GPU

Fast LZW Compression Using a GPU

引用

International Symposium on Computing and Networking (CANDAR)

作者： Shunji Funasaka Koji Nakano Yasuaki Ito Department of Information Engineering Hiroshima University Hiroshima Japan

The LZW compression is a well known patented lossless compression method used in Unix file compression utility "compress" and in GIF and TIFF image formats. It converts an input string of characters (or 8-bit unsigned integers) into a string of codes using a code table (or dictionary) that maps strings into codes. Since the code table is generated by repeatedly adding newly appeared substrings during the conversion, it is very hard to parallelize LZW compression. The main purpose of this paper is to accelerate LZW compression for TIFF images using a CUDA-enabled GPU. Our goal is to implement LZW compression algorithm using several acceleration techniques using CUDA, although it is a very hard task. Suppose that a GPU generates a resulting image generated by a computer graphics or image processing CUDA program and we want to archive it as a LZW-compressed TIFF image in the SSD connected to the host PC. We focused on the following two scenarios. Scenario~1: the resulting image is compressed using a GPU and written in the SSD through the host PC, and Scenario~2: it is transferred to the host PC, and compressed and written in the SSD using a CPU. The experimental results using NVIDIA GeForce GTX 980 and Intel Core i7 4790 show that Scenario 1 using our LZW compression implemented in a GPU is about 3 times faster than Scenario 2. From this fact, we can say that it makes sense to compress images using a GPU to archive them in the SSD.

关键词： Image coding Graphics processing units compression algorithms Instruction sets Dictionaries Acceleration Strips

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V-PFORDelta: Data compression for Energy Efficient Computation of Time Series

V-PFORDelta: Data Compression for Energy Efficient Computati...

引用

International Conference on High Performance Computing

作者： Abdullah Al Hasib Juan M. Cebrián Lasse Natvig Department of Computer and Information Science Norwegian University of Science and Technology Trondheim Norway

Chip multiprocessors (CMPs) and heterogeneous architectures have become predominant in all market segments, from embedded to high performance computing. These architectures exacerbate on-chip data requirements, creating additional pressure on the memory subsystem. Consequently, efficient utilization of on-chip memory space becomes critical for data intensive applications. A promising means of addressing this challenge is to use an effective compression method to reduce the data transmitted along the memory hierarchy. In this paper we present V-PFORDelta, a real-time vectorized integer differential compression method for memory bound applications. We evaluate the effectiveness of our SIMD (Single Instruction Multiple Data stream) based compression method on an industrial hydrological time series data processing kernel. We analyzed both Streaming SIMD Extensions (SSE) and Advanced Vector Extensions 2 (AVX2) versions of the compression method. Results show that the performance and energy efficiency can be improved up to a factor of 3.1 and 8.2, respectively. The proposed method not only outperforms the uncompressed SIMD implementations of the hydrological kernel, but also reduces the data storage requirements by a factor of 1.56x to 3.38x, depending on the analyzed dataset.

关键词： Encoding Time series analysis Kernel Data compression compression algorithms Memory management Parallel processing

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A Secure Video Deduplication Scheme in Cloud Storage Environments Using H.264 compression

A Secure Video Deduplication Scheme in Cloud Storage Environ...

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IEEE International Conference on Big Data Computing Service and Applications (BigDataService)

作者： Fatema Rashid Ali Miri Isaac Woungang Department of Computer Science Ryerson University Toronto Ontario Canada

Due to the rapidly increasing amounts of digital data produced worldwide, multi-user cloud storage systems are becoming very popular and Internet users are approaching cloud storage providers (CSPs) to upload their data in the clouds. Among these data, digital videos are fairly huge in terms of storage cost and size, and techniques that can help reducing the cloud storage cost and size are always desired. This paper argues that data reduplication can ease the problem of BigData storage by identifying and removing the duplicate copies from the cloud storages. Although reduplication maximizes the storage space and minimizes the storage costs, it comes with serious issues of data privacy and security. Though the users desire to save some cost by allowing the CSP to deduplicate their data, they do not want the CSP to wane the privacy of their data. In this paper, a scheme is proposed that achieves a secure video reduplication in cloud storage environments. Its design consists of embedding a partial convergent encryption along with a unique signature generation scheme into a H.264 video compression scheme. The partial convergent encryption scheme is meant to ensure that the proposed scheme is secured against a semi-honest CSP, the unique signature generation scheme is meant to enable a classification of the encrypted compressed video data in such a way that the reduplication can be efficiently performed on them. Experimental results and security analysis are provided to validate the stated goals.

关键词： Encryption Cloud computing Streaming media Transforms compression algorithms

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A novel DNA sequence compression scheme using both intra and inter sequences correlation

A novel DNA sequence compression scheme using both intra and...

引用

Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： K. O. Cheng N. F. Law W. C. Siu Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong

Classical DNA sequence compression algorithms consider only intra-sequence similarity, i.e., similar subsequences within the DNA sequence are found and encoded together. In this work, in addition to the intra-sequence similarity, we exploit the inter-sequence similarities in that similar subsequences are found within the DNA sequence as well as from other reference sequences. Hence, highly similar sequences from the same population or partially similar chromosome sequences of the same species can be compressed together to reduce the storage space. Experimental results show that the proposed scheme achieves good compressibility for both partially similar chromosome sequences and highly similar population sequences.

关键词： Biological cells DNA Encoding Sociology Statistics Decoding compression algorithms

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A Scalable High-Bandwidth Architecture for Lossless compression on FPGAs

A Scalable High-Bandwidth Architecture for Lossless Compress...

引用

Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM)

作者： Jeremy Fowers Joo-Young Kim Doug Burger Scott Hauck Microsoft Research Redmond WA US Department of Electrical Engineering University of Washington Seattle WA USA

Data compression techniques have been the subject of intense study over the past several decades due to exponential increases in the quantity of data stored and transmitted by computer systems. compression algorithms are traditionally forced to make tradeoffs between throughput and compression quality (the ratio of original file size to compressed file size). FPGAs represent a compelling substrate for streaming applications such as data compression thanks to their capacity for deep pipelines and custom caching solutions. Unfortunately, data hazards in compression algorithms such as LZ77 inhibit the creation of deep pipelines without sacrificing some amount of compression quality. In this work we detail a scalable fully pipelined FPGA accelerator that performs LZ77 compression and static Huffman encoding at rates up to 5.6 GB/s. Furthermore, we explore tradeoffs between compression quality and FPGA area that allow the same throughput at a fraction of the logic utilization in exchange for moderate reductions in compression quality. Compared to recent FPGA compression studies, our emphasis on scalability gives our accelerator a 3.0× advantage in resource utilization at equivalent throughput and compression ratio.

关键词： Hardware Computer architecture Field programmable gate arrays Throughput Pipelines Encoding compression algorithms

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