| 摘要: |
| 目的 为了解决传统的分形图像压缩算法计算量大和实时性差的问题， 提出一种改进的分形灰度图像压缩算法。方法 算法首先基于Gabor变换提取图像块的纹理特征， 然后基于K-means算法对R块和D块以纹理作为特征进行聚类处理， 并仅对同一类别的R块和D块进行匹配操作。结果 在候选块池的构造过程中， 文中提出了8种等距变换的简化算法。结论 文中方法能够在加快分形压缩速度的同时， 较好地保证重建图像的视觉效果， 具有较好的鲁棒性。 |
| 关键词: 图像压缩 分形理论 特征提取 |
| DOI： |
| 分类号:TS801 |
| 基金项目: |
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| Improved Fractal Gray Image Compression Algorithm |
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TIAN Xue-jun, SHU Zhong
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Jingchu University of Technology，Jingmen 448000，China
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| Abstract: |
| In order to solve the problems of the intensive computation and poor real-time property of conventional fractal image compression algorithm, this paper proposed an improved fractal gray image compression algorithm. Firstly, the algorithm used Gabor transform to extract texture features based on image blocks, then it used K-means algorithm to implement clustering process for R-block and D-block based on the texture features, and it only conducted matching operation for the R-block and D-block in the same category. In the construction process of the candidate blocks pool, this paper proposed a simplified algorithm for eight isometric transformations. The experimental results showed that this method could accelerate the speed of fractal compression, while ensure the visual effects of the reconstructed image with good robustness. |
| Key words: image compression fractal theory feature extraction |
