Fractional cycle spinning via modulated lapped transform for overcomplete image representation
Fractional cycle spinning via modulated lapped transform for overcomplete image representation
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DOI：
10.1109/icip.2014.7025539
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发表时间：
2014-01
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通讯作者：
Seisuke Kyochi;M. Ikehara
中科院分区：
文献类型：
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作者：
Seisuke Kyochi;M. Ikehara
提出了一种基于分数周期旋转(FCS)的过完备变换。与经典的临界采样小波变换不同，传统的小波变换的CS方法是为了实现具有冗余性的平移不变性。这一优势有助于高效的图像处理，例如图像去噪。所提出的FCS是对CS的推广，并表明输入信号的分数移位可以提供更丰富的超完备性。为了实现分数延迟，我们提出了基于调制重叠变换(MLT)的方法。结果表明，通过仔细选择窗函数，它们的滤波核可以表示任意分数延迟。此外，本文还将传统的最大似然变换扩展到二叉树最大似然变换，以改善其方向选择性差的问题。然后，为了降低计算复杂度，描述了一种高效的FCS格子结构。实验结果表明，FCS在图像去噪方面比传统CS有更好的应用效果。
This paper aims to introduce an overcomplete transform based on fractional cycle spinning (FCS). Conventionally, the CS approach of wavelet transforms has been proposed, in order to achieve translation invariance with redundancy, unlike the classical critically sampled wavelet transform. This advantage contributes to efficient image processing, such as image denoising. The proposed FCS generalizes CS and show that richer overcompleteness can be provided by fractional shifts of input signals. For realizing fractional delay, we present the approach based on modulated lapped transforms (MLTs). It is shown that their filter kernels can express arbitrary fractional delay by carefully selecting their window function. In addition, this paper extend the conventional MLT to the dual-tree MLT to improve its poor directional selectivity. Then, an efficient lattice structure for the FCS is described for lower computational complexity. Finally experimental results show FCS can be applied better than the conventional CS in image denoising.