光学相干层析成像
人工智能
计算机科学
灰度
计算
计算机视觉
Boosting(机器学习)
降噪
断层摄影术
连贯性(哲学赌博策略)
光学
图像(数学)
模式识别(心理学)
算法
数学
物理
统计
作者
Quan Zhou,Jingmin Guo,Mingyue Ding,Xuming Zhang
出处
期刊:Optics Letters
[Optica Publishing Group]
日期:2020-10-01
卷期号:45 (19): 5600-5600
被引量:10
摘要
This Letter presents a guided filtering (GF)-based nonlocal means (NLM) method for despeckling of optical coherence tomography (OCT) images. Unlike existing NLM methods that determine weights using image intensities or features, the proposed method first uses the GF to capture both grayscale information and features of the input image and then introduces them into the NLM for accurate weight computation. The boosting and iterative strategies are further incorporated to ensure despeckling performance. Experiments on the real OCT images demonstrate that our method outperforms the compared methods by delivering sufficient noise reduction and preserving image details well.
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