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A Bottom-Up Design Approach of Critically Sampled Contourlet Transform for Efficient Image Representation

机译:有效采样的临界采样Contourlet变换的自下而上设计方法

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In this paper, a novel design method of critically sampled contourlet transform (CSCT) is proposed. The original CT which consists of Laplacian pyramid and directional filter bank provides efficient frequency plane partition for image representation. However its overcom-pleteness is not suitable for some applications such as image coding, its critical sampling version has been studied recently. Although several types of the CSCT have been proposed, they have problems on their realization or unnatural frequency plane partition which is different from the original CT. In contrast to the way in conventional design methods based on a "top-down" approach, the proposed method is based on a "bottom-up" one. That is, the proposed CSCT decomposes the frequency plane into small directional subbands, and then synthesizes them up to a target frequency plane partition, while the conventional ones decompose into it directly. By this way, the proposed CSCT can design an efficient frequency division which is the same as the original CT for image representation can be realized. In this paper, its effectiveness is verified by non-linear approximation simulation.
机译:本文提出了一种新的临界采样轮廓波变换(CSCT)设计方法。由拉普拉斯金字塔和定向滤波器组组成的原始CT为图像表示提供了有效的频率平面划分。但是,它的过完全性不适用于某些应用,例如图像编码,最近已经研究了其临界采样版本。尽管已经提出了几种类型的CSCT,但是它们在实现上或与原始CT有所不同的频率平面划分方面存在问题。与基于“自上而下”方法的常规设计方法相比,所提出的方法基于“自下而上”方法。即,所提出的CSCT将频率平面分解成小的定向子带,然后将它们合成直到目标频率平面分区,而传统的则直接分解成目标频率平面分区。通过这种方式,所提出的CSCT可以设计有效的分频,该分频与可以实现用于图像表示的原始CT相同。本文通过非线性逼近仿真验证了其有效性。

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