28 March 2018 Speckle attenuation by adaptive singular value shrinking with generalized likelihood matching in optical coherence tomography
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Abstract
As a high-resolution imaging mode of biological tissues and materials, optical coherence tomography (OCT) is widely used in medical diagnosis and analysis. However, OCT images are often degraded by annoying speckle noise inherent in its imaging process. Employing the bilateral sparse representation an adaptive singular value shrinking method is proposed for its highly sparse approximation of image data. Adopting the generalized likelihood ratio as similarity criterion for block matching and an adaptive feature-oriented backward projection strategy, the proposed algorithm can restore better underlying layered structures and details of the OCT image with effective speckle attenuation. The experimental results demonstrate that the proposed algorithm achieves a state-of-the-art despeckling performance in terms of both quantitative measurement and visual interpretation.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Huaiguang Chen, Shujun Fu, Hong Wang, Hongli Lv, Caiming Zhang, "Speckle attenuation by adaptive singular value shrinking with generalized likelihood matching in optical coherence tomography," Journal of Biomedical Optics 23(3), 036014 (28 March 2018). https://doi.org/10.1117/1.JBO.23.3.036014 . Submission: Received: 5 December 2017; Accepted: 7 March 2018
Received: 5 December 2017; Accepted: 7 March 2018; Published: 28 March 2018
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