A Fast-lossless Compression Using Texture Prediction and Mixed Golomb Coding

LUO Yu; ZHANG Zhenzhen

doi:10.11999/JEIT170305

Volume 40 Issue 1

Jan. 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(1): 137-142

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. doi: 10.11999/JEIT170305

Citation:

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. doi: 10.11999/JEIT170305

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A Fast-lossless Compression Using Texture Prediction and Mixed Golomb Coding

doi: 10.11999/JEIT170305

LUO Yu¹,
ZHANG Zhenzhen²

1.
(Department of Basic Medicine, Shaanxi University of Chinese Medicine, Xi&rsquo
2.
(Institute of Systems, National University of Singapore, 119077, Singapore)

Funds:

The National 863 Program of China (2015M16903), The Natural Science Foundation of Shaanxi Province (2014k14-02-02)

Received Date: 2017-04-07
Rev Recd Date: 2017-07-07
Publish Date: 2018-01-19

Abstract

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.
- Chip,
- Fast,
- Lossless compression,
- Compression ratio,
- Coding time

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References(16)

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