A Frame Memory Lossless Compression Using Grain Directional Adaptive Prediction and Golomb Run-Length Entropy Coding

LUO Yu; TANG Bo

doi:10.3969/j.issn.0372-2112.2018.04.027

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A Frame Memory Lossless Compression Using Grain Directional Adaptive Prediction and Golomb Run-Length Entropy Coding

更新时间：2025-07-16

- A Frame Memory Lossless Compression Using Grain Directional Adaptive Prediction and Golomb Run-Length Entropy Coding
- Acta Electronica Sinica Vol. 46, Issue 4, Pages: 969-974(2018)
- 作者机构：
  
  1. 陕西中医药大学基础医学院,陕西,西安,712046
  2. 电子科技大学航天航空学院,四川,成都,611731
  3. 陕西中医药大学基础医学院,陕西,西安,712046
  4. 电子科技大学航天航空学院,四川,成都,611731
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2018.04.027
  CLC： TN919.81
- Published Online：25 April 2018，
  
  Published：2018
- 稿件说明：
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LUO Yu, TANG Bo. A Frame Memory Lossless Compression Using Grain Directional Adaptive Prediction and Golomb Run-Length Entropy Coding[J]. Acta Electronica Sinica, 2018, 46(4): 969-974.
DOI：

LUO Yu, TANG Bo. A Frame Memory Lossless Compression Using Grain Directional Adaptive Prediction and Golomb Run-Length Entropy Coding[J]. Acta Electronica Sinica, 2018, 46(4): 969-974. DOI： 10.3969/j.issn.0372-2112.2018.04.027.

摘要

为了进一步提高参考帧无损压缩的压缩性能，本文提出了一种基于纹理方向预测和游程哥伦布编码的帧存无损压缩算法.本算法首先采用双扫描和自适应预测的方法，按纹理方向，为每个像素选取最优的参考像素，并进行预测以获得预测残差；然后对预测残差进行哥伦布游程混合熵编码，从而提高了参考帧无损压缩的压缩性能.实现结果显示，与帧内预测哥伦布编码算法相比，本文算法不但平均压缩率提高了16%，而且降低了平均编码时间.

Abstract

To improve the compression performance

a frame memory lossless compression using grain-directional adaptive prediction and Golomb run-length entropy coding is proposed. First

the optimal reference pixels were obtained through double-scan and multi-directional prediction;then

the pixel differences were calculated and entropy-coded through Golomb and run-length. In this way

the compression performance is improved. Simulation results show that compared with those of reference frame lossless compression based on intra prediction and Golomb entropy coding

the average compression ratio is increased by 16% while the average coding time is reduced when using the proposed algorithm.

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