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Technology of Graphic & Image
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2485-2489

Sparse coding algorithm for fractal image compression based on coefficient of variation

Pang Huihui
Zhang Aihua
School of Science, Nanjing University of Posts & Telecommunications, Nanjing 210023, China

Abstract

Aiming at the problem of high complexity and long coding time of fractal image coding algorithm, the paper proposed orthogonal sparse coding and texture feature extraction to represent image blocks. Firstly, the orthogonal sparse transformation of gray level improved the image reconstruction quality and decoding time. Secondly, the correlation coefficient matrix measured the coefficient of variation characteristics between the range block and the domain block to reduce redundancy and coding time. The simulation results show that the proposed method has better image reconstruction quality and faster coding speed than the traditional fractal image coding algorithm.

Foundation Support

江苏省自然科学基金资助项目(BK20160880)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.08.0389
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 8
Section: Technology of Graphic & Image
Pages: 2485-2489
Serial Number: 1001-3695(2021)08-044-2485-05

Publish History

[2021-08-05] Printed Article

Cite This Article

庞慧慧, 张爱华. 基于变异系数的分形图像压缩稀疏编码算法 [J]. 计算机应用研究, 2021, 38 (8): 2485-2489. (Pang Huihui, Zhang Aihua. Sparse coding algorithm for fractal image compression based on coefficient of variation [J]. Application Research of Computers, 2021, 38 (8): 2485-2489. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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