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一种快速的纹理预测和混合哥伦布的无损压缩算法
引用本文:罗瑜,张珍珍.一种快速的纹理预测和混合哥伦布的无损压缩算法[J].电子与信息学报,2018,40(1):137-142.
作者姓名:罗瑜  张珍珍
作者单位:1.(陕西中医药大学基础医学院 西安 712046) ②(新加坡国立大学科学信息系统学院 新加坡 119077)
基金项目:国家863计划项目(2015M16903),陕西省自然科学基金(2014K14-02-02)
摘    要:为了进一步降低芯片内无损压缩的运算复杂度和编码时间,该文在保持高压缩率的基础上,提出一种基于方向预测和混合熵编码的快速无损压缩算法。该算法首先采用自适应方法进行纹理方向的预测,以获得当前像素的参考像素,并计算预测残差;然后对预测残差进行混合哥伦布编码,最终大幅度地提高了无损压缩的压缩性能。实验结果显示,与基于梯度预测和变长编码的无损压缩算法相比,该算法在平均压缩率略有提升的前提下,平均编码时间减少了36.86%。

关 键 词:芯片    快速    无损压缩    压缩率    编码时间
收稿时间:2017-04-07

A Fast-lossless Compression Using Texture Prediction and Mixed Golomb Coding
LUO Yu,ZHANG Zhenzhen.A Fast-lossless Compression Using Texture Prediction and Mixed Golomb Coding[J].Journal of Electronics & Information Technology,2018,40(1):137-142.
Authors:LUO Yu  ZHANG Zhenzhen
Affiliation:1.(Department of Basic Medicine, Shaanxi University of Chinese Medicine, Xi&rsquo2.(Institute of Systems, National University of Singapore, 119077, Singapore)
Abstract:A fast-lossless compression using texture prediction and mixed golomb coding is proposed to reduce the computational complexity while keeping high compression ratio. First, the reference pixel of the current pixel is gotten by texture direction prediction, meanwhile, the pixel difference is calculated. Then, the pixel difference is entropy coded through mixed Golomb. Thus, the compression performance is improved greatly. Simulation results show that compared with lossless frame memory compression using pixel gain prediction and dynamic order entropy coding, the proposed algorithm reduce the average coding time by 36.86%. Moreover, the average compression ratio is increased slightly in the proposed algorithm.
Keywords:
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