一种新的无损数据压缩预测编码粒子模型

First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06) Pub Date : 2006-06-20 DOI:10.1109/IMSCCS.2006.15

D. Shuai, Qing Shuai

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引用次数: 0

摘要

提出了一种新的广义粒子模型(GPM)来生成无损数据压缩的预测编码。讨论了GPM中粒子运动的局部规则、并行算法及其生成所需预测编码的实现结构。与其他顺序无损压缩方法相比，本文提出的GPM方法在编码速度、并行性、可伸缩性、简单性和易于硬件实现方面具有优势

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A New Particle Model For Prediction Coding of Lossless Data Compression

This paper presents a new generalized particle model (GPM) to generate the prediction coding for lossless data compression. Local rules for particle movement in GPM, parallel algorithm and its implementation structure to generate the desired predictive coding are discussed. The proposed GPM approach has advantages in terms of encoding speed, parallelism, scalability, simplicity, and easy hardware implementation over other sequential lossless compression methods

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First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06)

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