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Wavelet tree structure based speckle noise removal for optical coherence tomography

机译:基于小波树结构的散斑噪声去除技术

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We report a new speckle noise removal algorithm in optical coherence tomography (OCT). Though wavelet domain thresholding algorithms have demonstrated superior advantages in suppressing noise magnitude and preserving image sharpness in OCT, the wavelet tree structure has not been investigated in previous applications. In this work, we propose an adaptive wavelet thresholding algorithm via exploiting the tree structure in wavelet coefficients to remove the speckle noise in OCT images. The threshold for each wavelet band is adaptively selected following a special rule to retain the structure of the image across different wavelet layers. Our results demonstrate that the proposed algorithm outperforms conventional wavelet thresholding, with significant advantages in preserving image features.
机译:我们报告了一种新的光学相干断层扫描(OCT)的斑点噪声消除算法。尽管小波域阈值算法已显示出在OCT中抑制噪声幅度和保持图像清晰度的优越优势,但在先前的应用中尚未研究小波树结构。在这项工作中,我们提出了一种自适应小波阈值算法,该算法通过利用小波系数中的树结构来消除OCT图像中的斑点噪声。每个小波带的阈值是根据特殊规则自适应选择的,以跨不同小波层保留图像的结构。我们的结果表明,所提出的算法优于传统的小波阈值,在保留图像特征方面具有明显优势。

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