1. Feature-oriented singular value shrinkage for optical coherence tomography image

    Feature-oriented singular value shrinkage for optical coherence tomography image

    Optical coherence tomography (OCT) is a non-invasive optical imaging modality that has been widely used in the field of medical diagnosis. However, OCT images are often degraded by speckle noise. To address this problem, this paper proposes a two-stage feature-oriented singular value shrinkage algorithm in a low-rank approximation framework, for speckle noise reduction and contrast enhancement of intra-retinal layers of OCT images. First, a weighted absolute distance is employed to find nonlocal similar patches that exhibit high correlation to a given reference one. Next, the singular values of the group matrix formed by similar patches are shrunk by mixed thresholding ...

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