基于可分广义递归插值的三维无损压缩

B. Aiazzi, P. S. Alba, S. Baronti, L. Alparone
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引用次数: 25

摘要

在这项工作中,它表明,广义递归插值(GRINT)提出的是最有效的渐进式技术,帧间的层析切片的可逆压缩,通常发生在医学领域。图像序列以2倍的倍数抽取,首先只按行抽取,然后只按列抽取,最后只按片抽取,在后续中递归抽取,从而创建一个灰度级超金字塔,其体素数在每个级别上都减半。金字塔的顶部(根)被存储,然后通过一维核进行定向内插。与底层同等大小的超层的插值误差也被存储。重复同样的过程,直到图像序列被完全分解。与其他非因果DPCM方案相比,新方案的优点是:首先,对所有无误差的值进行插值,从而减小了残差的方差;其次,可以利用不同的行、列和段的相关值来进行更好的去相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Three-dimensional lossless compression based on a separable generalized recursive interpolation
In this work, it is shown that the generalized recursive interpolation (GRINT) proposed is the most effective progressive technique for inter-frame reversible compression of tomographic sections that typically occur in the medical field. An image sequence is decimated by a factor 2, first along rows only, then along columns only, and eventually along slices only, recursively in a sequel, thus creating a gray-level hyperpyramid whose number of voxels halves at every level. The top of the pyramid (root) is stored and then directionally interpolated by means of a 1D kernel. Interpolation errors with the underlying equally-sized hyperlayer are stored as well. The same procedure is repeated, until the image sequence is completely decomposed. The advantage of the novel scheme with respect to other noncausal DPCM schemes is twofold: firstly interpolation is performed from all error-free values, thereby reducing the variance of residuals; secondly different correlation values along rows, columns and sections can be exploited for a better decorrelation.
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