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检索条件"主题词=compression algorithms"

共 2082 条记录，以下是381-390 订阅

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Real time application of Raspberry Pi in compression of images

Real time application of Raspberry Pi in compression of imag...

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IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)

作者： S Sahitya H Lokesha L K Sudha Bangalore Institute of Technology Bengaluru-04 India National Aerospace Laboratories Bengaluru-17 India Bangalore Institute of Technology Bangalore Karnataka IN

ISBN: (纸本)9781509007752

An image contains large amount of digital data and it is necessary to reduce digital data volume for transmission and preservation by using image compression. This paper mainly concentrates on image compression using Raspberry Pi processor which helps to preserve large number of images and in retaining its quality. Raspberry Pi processor allows the implementation of most widely used 2-D Discrete Cosine Transform (DCT) compression method to give the Joint Photographic Experts Group (JPEG) format using Open CV platform. JPEG compression algorithm is used to compress the full-color still images which give good human visual perception (HVP) after the compression. Experimental results give the high quality compressed images and it is compared with different quality factors. Implementation of image compression on Raspberry Pi has its real time application of Micro Air Vehicles (MAVs). The proposed method helps MAVs to store large number of images captured by it.

关键词： Image coding Discrete cosine transforms compression algorithms Transform coding Quantization (signal) Standards Algorithm design and analysis

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High frame rate medical quality video compression for tele-EEG

High frame rate medical quality video compression for tele-E...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Laurent Lambert Syed Zahid Ahmed Khalil Hachicha Andrea Pinna Patrick Garda UPMC Univ Paris 06 Sorbonne Universités Paris France

ISBN: (纸本)9781457702198

More and more, exams require medical images as a tool to diagnose pathologies. Thus, the transfer and storage of the exam data becomes a critical issue. To address this issue, an image compression algorithm called Waaves has been developed and certified for medical imaging. Our work in this paper deals with a scenario of EEG exams where video of the patient is also recorded in order to correctly diagnose myoclonus pathologies. To achieve this goal, the video needs to be of high quality and at frame rate of at least 100 frames per second. This high data rate cannot be compressed on the fly by Waaves codec. In this paper, we present a novel codec based on the Waaves compression algorithm that fits the requirements of tele-video-EEG. We have used the characteristics of the input sequence and the analysis of the original codec, to improve the compression speed. The proposed video codec has shown a speed-up of around 3.4 times compared to the original algorithm. In addition, we have been able to improve the compression ratio while retaining necessary quality to identify myoclonus.

关键词： Codecs Discrete wavelet transforms Transform coding Image coding compression algorithms Bit rate Biomedical imaging

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Performance analysis of system-on-chip architectures for ultrasonic data compression

Performance analysis of system-on-chip architectures for ult...

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IEEE Symposium (IUS) Ultrasonics

作者： Boyang Wang Pramod Govindan Jafar Saniie Department of Electrical and Computer Engineering Illinois Institute of Technology Chicago Illinois School of Engineering University of North Florida Jacksonville Florida

ISBN: (纸本)9781467398985

Ultrasonic NDE and imaging applications utilize a large amount of information. Most of these applications demand real-time data processing with low power consumption. compression of the collected ultrasonic data helps to reduce the storage, as well as rapid data transmission to remote locations for expert analysis. The objective of this study is to develop embedded system-on-chip architectures for ultrasonic data compression, and analyze the performance of different design methods according to the application requirements. The system is implemented using Xilinx Zynq System-on-Chip (SoC), which combines both ARM processor and field-programmable gate array (FPGA) on the same chip. The major parameters analyzed in this study are signal fidelity, hardware resource utilization and computational processing speed. The hardware and software co-design implementation is about five times faster compared to software only implementation using Zynq SoC.

关键词： Acoustics Field programmable gate arrays Signal processing algorithms Finite impulse response filters Discrete wavelet transforms Random access memory compression algorithms

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Signal Characteristics on Sensor Data compression in IoT -An Investigation

Signal Characteristics on Sensor Data Compression in IoT -An...

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： Tulika Bose Soma Bandyopadhyay Sudhir Kumar Abhijan Bhattacharyya Arpan Pal TATA Consultancy Services Innovation Labs Kolkata India

ISBN: (纸本)9781509024308

In Internet of Things (IoT), numerous and diverse types of sensors generate a plethora of data that needs to be stored and processed with minimum loss of information. This demands efficient compression mechanisms where loss of information is minimized. Hence data generated by diverse sensors with different signal features require optimum balance between compression gain and information loss. This paper presents a unique analysis of contemporary lossy compression algorithms applied on real field sensor data with different sensor dynamics. The aim of the work is to classify the compression algorithms based on the signal characteristics of sensor data and to map them to different sensor data types to ensure efficient compression. The present work is the stepping stone for a future recommender system to choose the preferred compression techniques for the given type of sensor data.

关键词： sensor arrays array signal processing data compression Internet of Things Sensor Data Internet of things array signal processing Sensor arrays Data compression information loss compression algorithms Stepping Stones Recommender systems Sensors compression

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Biomedical signal compression with time- and subject-adaptive dictionary for wearable devices

Biomedical signal compression with time- and subject-adaptiv...

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IEEE Workshop on Machine Learning for Signal Processing

作者： Valentina Vadori Enrico Grisan Michele Rossi Dept. of Information Engineering University of Padova Italy

ISBN: (纸本)9781509007479

Wearable devices allow the seamless and inexpensive gathering of biomedical signals such as electrocardiograms (ECG), photoplethysmograms (PPG), and respiration traces (RESP). They are battery operated and resource constrained, and as such need dedicated algorithms to optimally manage energy and memory. In this work, we design SAM, a Subject-Adaptive (lossy) compression technique for physiological quasi-periodic signals. It achieves a substantial reduction in their data volume, allowing efficient storage and transmission, and thus helping extend the devices' battery life. SAM is based upon a subject-adaptive dictionary, which is learned and refined at runtime exploiting the time-adaptive self-organizing map (TASOM) unsupervised learning algorithm. Quantitative results show the superiority of our scheme against state-of-the-art techniques: compression ratios of up to 35-, 70- and 180-fold are generally achievable respectively for PPG, ECG and RESP signals, while reconstruction errors (RMSE) remain within 2% and 7% and the input signal morphology is preserved.

关键词： Dictionaries Neurons Indexes Training Runtime compression algorithms Quantization (signal)

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Progressive compression and transmission of 3D model with WebGL

Progressive compression and transmission of 3D model with We...

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International Conference on Audio, Language and Image Processing, ICALIP

作者： Pengfei Li XiaoQing Yu Jingjing Wang Institute of Smart City Shanghai University Shanghai China

ISBN: (纸本)9781509006557

This paper presents a system of progressive compression and transmission of 3D model with WebGL. The algorithm based on edge collapse is chosen in this system to complete the compression work and is modified in order to adapt the system. WebGL is used in the client part of the system so the system could be multi-platform as long as the browser supports the HTML5 on that platform, like chrome, firefox and so on. These browsers supported almost all the platform. With the progressive compression method running on the server side and WebGL technology running on the browser, people can get the view of the 3D models in much more quickly even on the smartphone as well as the quality of the models still can be accepted.

关键词： Three-dimensional displays Browsers Servers Data models Solid modeling Computational modeling compression algorithms

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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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MLC: An Efficient Multi-level Log compression Method for Cloud Backup Systems

MLC: An Efficient Multi-level Log Compression Method for Clo...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Bo Feng Chentao Wu Jie Li Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Department of Computer Science University of Tsukuba Tsukuba Ibaraki Japan

ISBN: (纸本)9781509032068

With the rapid development of Internet and cloud services, logs become one of the fastest growing data types in backup storage systems. These massive data always require long-term storage, which incurs high storage overhead. Typical compression algorithms, such as traditional lossless compression and log-specific compression algorithms, are employed to increase storage efficiency. However, these algorithms ignore the inherent semantics of logs, particularly for the well-structured compositions within log records and the striking similarities among them. Therefore, they cannot guarantee a satisfactory compression ratio. To address this problem, we propose a novel Multi-level Log compression (MLC) method for cloud backup systems. MLC can achieve high compression ratio for various applications and workloads. Different from existing compression algorithms, MLC first explores data redundancy among log records and divides them into different buckets in accordance with their similarities. Then, the log records are condensed by a variation of delta compression. After that, a traditional compression algorithm is employed as the secondary compression to further improve the compression ratio. To demonstrate the effectiveness of MLC, we conduct several experiments under different log workloads. The results show that, MLC improves the compression ratio of 7zip, gzip and bzip2 by up to 30.3%, 26.8% and 16.1%, respectively.

关键词： compression algorithms Cloud computing Semantics Indexes Redundancy Algorithm design and analysis Computer science

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A case for toggle-aware compression for GPU systems

A case for toggle-aware compression for GPU systems

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IEEE Symposium on High-Performance Computer Architecture

作者： Gennady Pekhimenko Evgeny Bolotin Nandita Vijaykumar Onur Mutlu Todd C. Mowry Stephen W. Keckler Carnegie Mellon University NVIDIA Carnegie Mellon University Pittsburgh PA US University of Texas at Austin

ISBN: (纸本)9781467392129

Data compression can be an effective method to achieve higher system performance and energy efficiency in modern data-intensive applications by exploiting redundancy and data similarity. Prior works have studied a variety of data compression techniques to improve both capacity (e.g., of caches and main memory) and bandwidth utilization (e.g., of the on-chip and off-chip interconnects). In this paper, we make a new observation about the energy-efficiency of communication when compression is applied. While compression reduces the amount of transferred data, it leads to a substantial increase in the number of bit toggles (i.e., communication channel switchings from 0 to 1 or from 1 to 0). The increased toggle count increases the dynamic energy consumed by on-chip and off-chip buses due to more frequent charging and discharging of the wires. Our results show that the total bit toggle count can increase from 20% to 2.2x when compression is applied for some compression algorithms, averaged across different application suites. We characterize and demonstrate this new problem across 242 GPU applications and six different compression algorithms. To mitigate the problem, we propose two new toggle-aware compression techniques: Energy Control and Metadata Consolidation. These techniques greatly reduce the bit toggle count impact of the data compression algorithms we examine, while keeping most of their bandwidth reduction benefits.

关键词： Bandwidth Data compression System-on-chip Graphics processing units compression algorithms Data transfer Random access memory

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A low-power area-efficient design and comparative analysis for high-resolution neural data compression

A low-power area-efficient design and comparative analysis f...

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International Conference on Microelectronics, ICM

作者： Mohammed Ashraf Hassan Mostafa Ahmed A. El-Adawy Electronics and Communications Engineering Department Cairo Universitv Giza Egypt Center for Nanoelectronics and Devices AUC and Zewail City of Science and Technology New Cairo Egypt

Nowadays, brain scientific research progress depends on signal compression at high spatial resolutions, for efficient storage and low-rate transmission through wireless connection to outside world. So that neural data compression at the implant site is necessary in order to conform with the wireless rates restrictions. In this paper, the high spatial correlation is utilized to increase the data compression ratio. Then we investigate and compare three different proposed low-power image compression algorithms based on discrete cosine transform (DCT) and discrete wavelet transform (DWT) to provide the best trade-off between hardware complexity and compression performance. Hence, we conclude that Adaptive 2D-DWT algorithm is a promising solution for low-power implantable devices.

关键词： Discrete wavelet transforms compression algorithms Hardware Quantization (signal) Correlation Discrete cosine transforms Spatial resolution

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