Clustering context properties of wavelet coefficients in automatic modelling and image coding

J. Lehtinen, J. Kivijärvi
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Abstract

An algorithm for automatic modelling of wavelet coefficients from context properties is presented. The algorithm is used to implement an image coder, in order to demonstrate its image coding efficiency. The modelling of wavelet co-efficients is performed by partitioning the weighted context property space to regions. Each of the regions has a dynamic probability distribution stating the predictions of the modeled co-efficients. The coding performance of the algorithm is compared to other efficient wavelet-based image compression methods.
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小波系数在自动建模和图像编码中的聚类上下文特性
提出了一种基于上下文属性的小波系数自动建模算法。用该算法实现了一个图像编码器,以验证其图像编码效率。小波系数的建模是通过将加权的上下文属性空间划分为区域来实现的。每个区域都有一个动态概率分布,说明模型系数的预测。将该算法的编码性能与其他有效的基于小波的图像压缩方法进行了比较。
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