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Hardware Based Data Compression using Lempel-Ziv-Welch Algorithm
Published in Durgesh Kumar Mishra, Nilanjan Dey, Bharat Singh Deora, Amit Joshi, ICT for Competitive Strategies, 2020
Onkar Choudhari, Marisha Chopade, Sourabh Chopde, Vaishali Ingle
Data compression is the art of deducting the amount of bits required to store or transmit the given information, using encoding techniques. The primary aim of data compression is to eliminate redundancy. The design of data compression algorithms involves trade-offs among factors like, the compression ratio, amount of distortion introduced and the computational resources required to compress and decompress the data[1]. Lossy and lossless are the two ways in which compression can take place. The amount of data is reduced in lossless compression by identifying and removing statistical redundancy. No information is lost in lossless compression. For text compression lossless compression techniques are used. Lossy compression reduces data by eliminating unnecessary or less important information. Lossy compression is typically used for images[2] and audio where a little bit of loss in resolution is often undetectable and acceptable.
Network Models
Published in Sunit Kumar Sen, Fieldbus and Networking in Process Automation, 2017
Syntax and semantics of a data message are taken care of by the presentation layer. Figure 3.12 shows the operation of a presentation layer. Its responsibilities include the following: It is the responsibility of the presentation layer to ensure that data encoded differently by different computers are interoperable.Sensitive information, to be exchanged between the sender and the receiver, must be kept away from possible eavesdroppers. Data is encrypted in a manner that hides the information from such malafide data poachers. Decryption is done to transform the message back to its original form at the receiver.Data compression is a method that reduces the bit numbers contained in a data stream, without losing vital information. It is particularly applied in multimedia systems.
Satellite Imaging and Sensing
Published in John G. Webster, Halit Eren, Measurement, Instrumentation, and Sensors Handbook, 2017
Data compression is one of the most important tools to overcome the problems of data transmission, storage, and dissemination [43]. Data compression methods are usually classified as either lossless or lossy. With a lossless data compression scheme, the original data can be reconstructed exactly without any loss; in a lossy compression scheme, original data are reconstructed with a degree of error. For transmission from the satellite to the ground station, a lossless data compression must be utilized. For browsing purposes, lossy compression enables quick searches through large amounts of data. A compression scheme is also characterized by its compression ratio, that is, the factor by which the amount of information which represents the data is reduced through compression. For earth science data, lossless compression schemes provide compression ratios up to 2 or 3, while lossy techniques can reduce the amount of information by a factor of 20 or more without degrading the visual quality of the data.
A Novel Hybrid Medical Data Compression Using Huffman Coding and LZW in IoT
Published in IETE Journal of Research, 2022
Hossein Mohammadi, Abdulbaghi Ghaderzadeh, Amir Sheikh Ahmadi
We are living in the age of high information and communication technology, and have long-standing problem of improving human health in healthcare systems. The History of Telemedicine provides a comprehensive and in-depth historical view of telemedicine from ancient Greece to the present time. Telemedicine is a method, by which patients can be examined, investigated, monitored and treated, with the patient and the doctor located in different places. Telemedicine hinges on transfer of text, reports, voice, images and video, between geographically separated locations. Medical data may contain X-ray, MRI, CT-scan, Ultra sound images, Blood slide, ECG signal, pathological reports and Audio-video clippings. Data compression techniques have been widely used to process and transmit huge amount of data in real-time and remote signal processing systems.
Big data-enabled intelligent synchronisation for the complex production logistics system under the opti-state control strategy
Published in International Journal of Production Research, 2022
Kai Zhang, Ting Qu, Yongheng Zhang, Ray Y. Zhong, George Huang
The cleaned data cube is still huge, which will affect the efficiency of subsequent data transmission IO. Therefore, it is necessary to compress the data of the cleaned cube. Data compression usually refers to a technology that compresses the data volume or reorganises the data through some algorithms without losing valid data. For example, every machine has a unique machine ID, represents the capacity of machine, is a boolean variable that stands for the use status of machine, and the current available equipment capacity is recorded as available machine capabilities, AMC, then . If use AMC to replace original data include , and Machine ID, it will reduce the dimensions and volume of the data cube. Data classification
Some invariant and inverse invariant characters of information systems under homomorphisms based on data compression
Published in International Journal of General Systems, 2020
Data compression in information systems is referred to two aspects of operations on data, one is to reduce data dimension, the other is to reduce stored and transferred data volume. Reducing data dimension can be explained as reductions of information systems. Reducing data volume can be viewed as a many-to-one mapping between information systems in mathematics, while homomorphism between information systems, introduced by Li and Ma (2000), is this mapping. They showed that reductions and dispensable attribute in information systems are invariant under homomorphisms. This homomorphism may be a tool for studying data compression in information systems. A complex massive information system can be compressed into a relatively small-scale information system by means of homomorphisms. Meanwhile, some of the same data structures in information systems are maintained.