Abstract
To address the problem of long coding time of fractal image compression algorithm, this paper proposes a fractal image compression algorithm based on compression perception. Firstly, the algorithm is coded in the wavelet domain by separating the high and low frequency signals of the image, then, the low frequency information is fractally coded, while the sparse high frequency signals are sampled and coded in a compression-aware manner, and finally, a better image reconstruction compensation effect is achieved with the premise of reducing the number of coding searches and coding time. The experimental results show that this algorithm has a slight decrease in coding quality and compression ratio compared to fractal coding image compression, but has a superior improvement in coding speed.
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Acknowledgments
Supported by a project grant from National Natural Science Foundation (Grand No. 61961036 & 62162054), the University Young Teachers Basic Ability Improvement Project of Guangxi (Grand No. 2018KY0537 & 2017KY0629), Wuzhou Scientific Research and Technology Development Project (Grand No. 201501014), Guangxi Natural Science Foundation (Grand No. 2020GXNSFAA297259 & 2018GXNSFBA281173), Wuzhou High-tech Zone, Wuzhou University Industry-Education-Research Project (Grand No. 2020G001), the Guangxi Innovation-Driven Development Special Driven Develop Special Fund Project (Guike AA18118036), the Guangxi Science and Technology Base and Talent Special Project (Guike AD20297148).
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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zhang, L., Xu, C., He, J. (2022). Fast Fractal Image Compression Algorithm Based on Compression Perception. In: Jiang, X. (eds) Machine Learning and Intelligent Communications. MLICOM 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 438. Springer, Cham. https://doi.org/10.1007/978-3-031-04409-0_27
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DOI: https://doi.org/10.1007/978-3-031-04409-0_27
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