使用基于层的表示的多视图图像压缩

Andriy Gelman, P. Dragotti, V. Velisavljevic
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引用次数: 18

摘要

提出了一种新的多视点图像压缩方法。该算法利用基于层的表示,将数据集划分为以恒定深度值为特征的平面层。为了提高压缩效率,使用可分离的三维小波变换跨视点和空间维度去相关。对变换进行了改进,以有效地处理不同深度的遮挡和视差变化。生成的变换系数是熵编码的。实验结果表明,对于不同的数据集,我们的编码方法能够优于最先进的算法,如H.264/AVC。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiview image compression using a layer-based representation
We propose a novel compression method for multiview images. The algorithm exploits the layer-based representation, which partitions the data set into planar layers characterized by a constant depth value. For efficient compression, the partitioned data is decorrelated using the separable three-dimensional wavelet transform across the viewpoint and spatial dimensions. The transform is modified to efficiently deal with occlusions and disparity variations for different depths. The generated transform coefficients are entropy coded. Experimental results show that our coding method is capable of outperforming the state-of-the-art algorithms, like H.264/AVC, for different data sets.
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