利用最近邻估计的分形特征压缩图像

M. Jampour, Maryam Ashourzadeh, M. Yaghoobi, Issa Rashidfarokhi
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引用次数: 6

摘要

本文介绍了一种利用分形特征进行图像压缩的新技术。图像压缩在数据存储和转换中是极其重要和有价值的,因此研究人员一直在寻找不同的技术来解决这一问题。在本文中,我们使用了一种组合估计最近邻的方法,并借助自适应方法来评估图像大小的范围,提出了一种压缩图像的解决方案,首先是在检索后的最终图像是合适的,其次是在块邻近区域中选择合适的边界以及选择所选块的大小,算法执行速度相对于所介绍的方法。质量也有所提高。该方法在Matlab平台上对多幅图像进行了实现,分析结果表明该方法相对于其他方法有所改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Compressing Images Using Fractal Characteristics by Estimating the Nearest Neighbor
In this paper a new technique have been introduced for image compression using Fractal characteristics. Compressing images in data storage and transformation is extremely important and valuable, for this reason researchers are always looking for different techniques to resolve this issue. In this paper we have used a combined method of estimating nearest neighbor, and with the help of an adaptive method to evaluate the Range of image sizes, a solution for compressing images is introduced which first the final image is appropriate after it is retrieved, second with respect to the selection of appropriate boundary in the blocks neighborhood along with the selection of sizes for picked blocks, the speed of algorithm execution with respect to the methods introduced, and also the quality has improved respectively. This method has been implemented in the Matlab platform on several images, and the analysis shows the improvement respective to other methods.
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