Chen Huaiguang, Gao Jing
School of Science, Shandong Jianzhu University, Jinan 250101, China.
Center for Engineering Computation and Software Development, Shandong Jianzhu University, Jinan 250101, China.
Micromachines (Basel). 2022 Nov 22;13(12):2039. doi: 10.3390/mi13122039.
Optical coherence tomography (OCT) is used in various fields such, as medical diagnosis and material inspection, as a non-invasive and high-resolution optical imaging modality. However, an OCT image is damaged by speckle noise during its generation, thus reducing the image quality. To address this problem, a non-local means (NLM) algorithm based on the fractional compact finite difference scheme (FCFDS) is proposed to remove the speckle noise in OCT images. FCFDS uses more local pixel information when compared to integer-order difference operators. The FCFDS operator is introduced into the NLM algorithm to construct a high-precision weight calculation so that the proposed algorithm can effectively reduce the speckle noise in the OCT images. Experiments on simulations and real OCT images show that the proposed method is comparable to other state-of-the-art despeckling methods and can substantially reduce noise and preserve image details such as edges and structures. Speckle noise removal can further promote the application of the proposed algorithm in medical diagnosis and industrial detection, as it has key research value.
光学相干断层扫描（OCT）作为一种非侵入性的高分辨率光学成像方式，被应用于医学诊断和材料检测等各个领域。然而，OCT图像在生成过程中会受到散斑噪声的影响，从而降低图像质量。为了解决这个问题，提出了一种基于分数紧致有限差分格式（FCFDS）的非局部均值（NLM）算法来去除OCT图像中的散斑噪声。与整数阶差分算子相比，FCFDS使用了更多的局部像素信息。将FCFDS算子引入NLM算法中，构建高精度的权重计算，使得所提出的算法能够有效降低OCT图像中的散斑噪声。对模拟图像和实际OCT图像的实验表明，该方法与其他现有去噪方法相当，能够大幅降低噪声并保留边缘和结构等图像细节。散斑噪声去除可以进一步推动所提出算法在医学诊断和工业检测中的应用，具有关键的研究价值。
