检索结果-内蒙古大学图书馆

International Symposium on Image and Signal Processing and Analysis

作者： N.I. Glumov Image Processing Systems Institute of the RAS Samara Russia

The problem of compression and error-control coding algorithms for digital image transmission through communication channels is considered. The criteria of the output image quality are discussed, and a technique for modeling faults in communication channels is proposed. In an example of the compression method based on hierarchical grid interpolation, a possibility of significant increase of noise immunity of compressed images is shown.

关键词： Image coding Digital images Communication channels Signal processing algorithms compression algorithms Error correction codes Interpolation Stability Redundancy Image processing

来源：评论

学校读者我要写书评

暂无评论

Multi-Channel Data Structure and Real-Time compression Algorithm Research

引用

IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE 2009年第11期24卷 28-35页

作者： Ren, Yongfeng Liu, Xiaohua Xu, Wenqiang Zhang, Wendong N Univ China Natl Key Lab Elect Measurement Technol Key Lab Instrumentat Sci & Dynam Measurement Minist Educ Taiyuan 030051 Peoples R China

The development of space telemetry technology has brought forward the need for large capacity memory of any solid-state recorder;data compression therefore, becomes more and more important. The compression feasibility and potentiality of telemetry data are examined by analyzing the statistical characteristics of actual telemetry data recovered from recorders. Aiming at the disadvantage of present data formats in data compression for multi-channel telemetry data acquisition systems, this introduces a data packet structure, and a real-time compression algorithm for low complex hardware design. The principles and implementations of data package compression are described. Simulation results show that this technology can meet the requirements of multi-channel real-time data compression with a high compression ratio and a fast compression speed, which possesses great application value.

关键词： Telemetry compression algorithms Hardware Data compression Encoding Real time systems

来源：评论

学校读者我要写书评

暂无评论

XCQ: A queriable XML compression system

引用

KNOWLEDGE AND INFORMATION SYSTEMS 2006年第4期10卷 421-452页

作者： Ng, Wilfred Lam, Wai-Yeung Wood, Peter T. Levene, Mark Hong Kong Univ Sci & Technol Dept Comp Sci Kowloon Hong Kong Peoples R China Univ London Sch Comp Sci & Informat Syst London England

XML has already become the de facto standard for specifying and exchanging data on the Web. However, XML is by nature verbose and thus XML documents are usually large in size, a factor that hinders its practical usage, since it substantially increases the costs of storing, processing, and exchanging data. In order to tackle this problem, many XML-specific compression systems, such as XMill, XGrind, XMLPPM, and Millau, have recently been proposed. However, these systems usually suffer from the following two inadequacies: They either sacrifice performance in terms of compression ratio and execution time in order to support a limited range of queries, or perform full decompression prior to processing queries over compressed documents. In this paper, we address the above problems by exploiting the information provided by a Document Type Definition (DTD) associated with an XML document. We show that a DTD is able to facilitate better compression as well as generate more usable compressed data to support querying. We present the architecture of the XCQ, which is a compression and querying tool for handling XML data. XCQ is based on a novel technique we have developed called DTD Tree and SAX Event Stream Parsing (DSP). The documents compressed by XCQ are stored in Partitioned Path-Based Grouping (PPG) data streams, which are equipped with a Block Statistics Signature (BSS) indexing scheme. The indexed PPG data streams support the processing of XML queries that involve selection and aggregation, without the need for full decompression. In order to study the compression performance of XCQ, we carry out comprehensive experiments over a set of XML benchmark datasets.

关键词： XML document type definitions compression algorithms query processing performance

来源：评论

学校读者我要写书评

暂无评论

A 65-nm CMOS Lossless Bio-Signal compression Circuit With 250 FemtoJoule Performance Per Bit

引用

IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2019年第5期13卷 1087-1100页

作者： Crispin-Bailey, Christopher Dai, Chenglaing Austin, Jim Univ York Dept Comp Sci York YO10 5GH N Yorkshire England Imperial Coll London London SW7 2AZ England

A 65nm CMOS integrated circuit implementation of a bio-physiological signal compression device is presented, reporting exceptionally low power, and extremely low silicon area cost, relative to state-of-the-art. A novel 'xor-log2-sub-band' data compression scheme is evaluated, achieving modest compression, but with very low resource cost. With the intent to design the simplest useful compression algorithm', the outcome is demonstrated to be very favourable where power must be saved by trading off compression effort against data storage capacity, or data transmission power, even where more complex algorithms can deliver higher compression ratios. A VLSI design and fabricated Integrated Circuit implementation are presented, and estimated performance gains and efficiency measures for various bio-medical use-cases are given. Power costs as low as 1.2 pJ per sample-bit are suggested for a 10kSa/s data-rate, whilst utilizing a power-gating scenario, and dropping to 250fJ/bit at continuous conversion data-rates of 5MSa/sec. This is achieved with a diminutive circuit area of 155um(2). Both power and area appear to be state-of-the-art in terms of compression versus resource cost, and this yields benefit for system optimization.

关键词： Encoding Integrated circuits Data compression compression algorithms Biomedical measurement Hardware ECG EEG lossless data compression power efficiency VLSI design wearable sensors

来源：评论

学校读者我要写书评

暂无评论

HADC: A Hybrid compression Approach for DNA Sequences

引用

IEEE ACCESS 2022年 10卷 106841-106848页

作者： Elnady, Sarah Sayed, Sabah Salah, Akram Cairo Univ Fac Comp & Artificial Intelligence Comp Sci Dept Cairo 12613 Egypt

In the blossoming age of Next Generation Sequencing (NGS) technologies, genome sequencing has become much easier and more affordable. The large number of enormous genomic sequences obtained demand the availability of huge storage space in order to be kept for analysis. Since the storage cost has become an impediment facing biologists, there is a constant need of software that provides efficient compression of genomic sequences. Most general-purpose compression algorithms do not exploit the inherent redundancies that exist in genomic sequences which is the reason for the success and popularity of reference-based compression algorithms. In this research, a new reference-based lossless compression technique is proposed for deoxyribonucleic acid (DNA) sequences stored in FASTA format which can act as a layer above gzip compression. Several experiments were performed to evaluate this technique and the experimental results show that it is able to obtain promising compression ratios saving up to 99.9% space and reaching a gain of 80% for some plant genomes. The proposed technique also succeeds in performing the compression at acceptable time;even saving more than 50% of the time taken by ERGC in most experiments.

关键词： Bioinformatics Genomics DNA Sequential analysis compression algorithms Encoding Redundancy Bioinformatics DNA sequences reference-based compression greedy alignment

来源：评论

学校读者我要写书评

暂无评论

Joint-Way compression for LDPC Neural Decoding Algorithm With Tensor-Ring Decomposition

引用

IEEE ACCESS 2023年 11卷 22871-22879页

作者： Liang, Yuanhui Lam, Chan-Tong Ng, Benjamin K. Macao Polytech Univ Fac Appl Sci Macau 999078 Peoples R China

In this paper, we propose low complexity joint-way compression algorithms with Tensor-Ring (TR) decomposition and weight sharing to further lower the storage and computational complexity requirements for low density parity check (LDPC) neural decoding. Compared with Tensor-Train (TT) decomposition, TR decomposition is more flexible for the selection of ranks, and is also conducive to the use of rank optimization algorithms. In particular, we use TR decomposition to decompose not only the weight parameter matrix of Neural Normalized Min-Sum (NNMS)+ algorithm, but also the message matrix transmitted between variable nodes and check nodes. Furthermore, we combine the TR decomposition and weight sharing algorithm, called joint-way compression, to further lower the complexity of LDPC neural decoding algorithm. We show that the joint-way compression algorithm can achieve better compression efficiency than a single compression algorithm while maintaining a comparable bit error rate (BER) performance. From the numerical experiments, we found that all the compression algorithms with appropriate selection of ranks give almost no performance degradation and that the TRwm-ssNNMS+ algorithm, which combines the spatial sharing and TR decomposition of both weight and message matrix, has the best compression efficiency. Compared with our TT-NNMS+ algorithm proposed in Yuanhui et al. (2022), the number of parameters is reduced by about 70 times and the number of multiplications is reduced by about 6 times.

关键词： Decoding Artificial neural networks Iterative decoding Tensors Matrix decomposition compression algorithms Training Joint-way compression weight sharing tensor ring decomposition LDPC neural decoding

来源：评论

学校读者我要写书评

暂无评论

Sub-block interchange for lossless image compression

引用

IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 1999年第1期45卷 236-242页

作者： Ng, KS Cheng, LM City Univ Hong Kong Dept Elect Engn Kowloon SAR Hong Kong Peoples R China

Lempel-Ziv-Welch (LZW) technique for text compression has been successfully modified to lossless image compression such as GIF. Recently, a new class of text compression, namely, Burrows and Wheeler Transformation (BWT) has been developed which gives promising results for text compression. Here, we propose a sub-block interchange lossless compression method which belongs to this block sorting class. Our compression results have outperformed GIF in compression ratios and BWT in compression times when tested with 512x512 pixel 8-bit grey scale images. The comparison of compression ratios and times with GIF, BWT and other popular LZ based compression methods are discussed.

关键词： Image coding Sorting Testing Pixel compression algorithms Data compression Performance loss Decoding Entropy coding

来源：评论

学校读者我要写书评

暂无评论

An Energy-Efficient compression Algorithm of ECG Signals in Remote Healthcare Monitoring Systems

引用

IEEE ACCESS 2022年 10卷 39129-39144页

作者： Fathi, Islam S. Makhlouf, Mohamed Abd Allah Osman, Elsaeed Ahmed, Mohamed Ali Suez Canal Univ Fac Sci Dept Math Ismailia 41522 Egypt Suez Canal Univ Fac Comp & Informat Dept Informat Syst Ismailia 41522 Egypt Nanda Univ Fac Comp Sci Bani Suwayf 62521 Egypt Al Azhar Univ Fac Engn Dept Elect Engn Cairo 11651 Egypt

Remote Healthcare Monitoring Systems (RHMs) that use ECG signals are very effective tools for the early diagnosis of various heart conditions. However, these systems are still confronted with a problem that reduces their efficiency, such as energy consumption in wearable devices because they are battery-powered and have limited storage. This paper presents a novel algorithm for the compression of ECG signals to reduce energy consumption in RHMs. The proposed algorithm uses discrete Krawtchouk moments as a feature extractor to obtain features from the ECG signal. Then the accelerated Ant Lion Optimizer (AALO) selects the optimum features that achieve the best-reconstructed signal. Our proposed algorithm is extensively validated using two benchmark datasets: MIT-BIH arrhythmia and ECG-ID. The proposed algorithm provides the average values of compression ratio (CR), percent root mean square difference (PRD), signal to noise ratio (SNR), Peak Signal to noise ratio (PSNR), and quality score (QS) are 15.56, 0.69, 44.52, 49.04 and 23.92, respectively. The comparison demonstrates the advantages of the proposed compression algorithm on recent algorithms concerning the mentioned performance metrics. It also tested and compared against other existing algorithms concerning Processing Time, compression speed and computational efficiency. The obtained results show that the proposed algorithm extremely outperforms in terms of (Processing Time = 6.89 s), (compression speed = 4640.19 bps) and (computational efficiency = 2.95). The results also indicate that the proposed compression algorithm reduces energy consumption in a wearable device by decreasing the wake-up time by 3600 ms.

关键词： Electrocardiography Medical services Encoding compression algorithms Data compression Discrete wavelet transforms Sensors Remote healthcare monitoring signal compression electrocardiogram (ECG) energy efficiency krawtchouk moments Ant Lion Optimizer

来源：评论

学校读者我要写书评

暂无评论

Near lossless data compression onboard a hyperspectral satellite

引用

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2006年第3期42卷 851-866页

作者： Qian, Shen-En Bergeron, Martin Cunningham, Ian Gagnon, Luc Hollinger, Allan Canadian Space Agcy St Hubert PQ J3Y 8Y9 Canada Dettwiler & Associates Corp Space Div Ste Anne De Bellevue PQ H9X 3R2 Canada

To deal with the large volume of data produced by hyperspectral sensors, the Canadian Space Agency (CSA) has developed and patented two near lossless data compression algorithms for use onboard a hyperspectral satellite: successive approximation multi-stage vector quantization (SAMVQ) and hierarchical self-organizing cluster vector quantization (HSOCVQ). This paper describes the two compression algorithms and demonstrates their near lossless feature. The compression error introduced by the two compression algorithms was compared with the intrinsic noise of the original data that is caused by the instrument noise and other noise sources such as calibration and atmospheric correction errors. The experimental results showed that the compression error was not larger than the intrinsic noise of the original data when a test data set was compressed at a compression ratio of 20:1. The overall noise in the reconstructed data that contains both the intrinsic noise and the compression error is even smaller than the intrinsic noise when the data is compressed using SAMVQ. A multi-disciplinary user acceptability study has been carried out in order to evaluate the impact of the two compression algorithms on hyperspectral data applications. This paper briefly summarizes the evaluation results of the user acceptability study. A prototype hardware compressor that implements the two compression algorithms has been built using field programmable gate arrays (FPGAs) and benchmarked. The compression ratio and fidelity achieved by the hardware compressor are similar to those obtained by software simulation.

关键词： compressors field programmable gate arrays geophysical signal processing image coding remote sensing vector quantisation HSOCVQ SAMVQ compression error hierarchical self organizing cluster vector quantization hyperspectral Compressors geophysical signal processing image coding Field programmable gate arrays Vector quantization remote sensing instrument noise intrinsic noise RAW DATA compression algorithms compression ratio

来源：评论

学校读者我要写书评

暂无评论

SPECTRAL AND SPATIAL DECORRELATION OF LANDSAT-TM DATA FOR LOSSLESS compression

引用

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1995年第5期33卷 1277-1285页

作者： WANG, JF ZHANG, KH TANG, SW UNIV WESTERN ONTARIO DEPT COMP SCILONDONON N6A 5B7CANADA BEIJING COMP INST DEPT COMP SCIBEIJINGPEOPLES R CHINA

This paper presents some new techniques of spectral and spatial decorrelation in lossless data compression of remotely sensed imagery. These techniques provide methods to efficiently compute the optimal band combination and band ordering based on the statistical properties of Landsat-TM data. Experiments on several Landsat-TM images show that using both the spectral and the spatial nature of the remotely sensed data results in significant improvement over spatial decorrelation alone. These techniques result in higher compression ratios and are computationally inexpensive.

关键词： Decorrelation Satellites Remote sensing Image coding Data compression Computer science Reflectivity Image reconstruction compression algorithms Councils

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：