激光与光电子学进展, 2020, 57 (22): 221005, 网络出版: 2020-11-03
光热光学相干层析成像中基于小波变换的旋转核变换去噪算法
Rotating Kernel Transformation Denoising Algorithm Based on Wavelet Transform in Photothermal Optical Coherence Tomography
摘要
针对光热光学相干层析(PT-OCT)三维图像中有不同类型的散斑噪声,采用改进的旋转核算法对其进行抑制。首先对PT-OCT图像进行小波分解,获得4个不同频带的子图像;然后利用最大类间方差算法分离低频近似子图像的前景和背景,并对其进行分段增强,使用改进的RKT算法分别对水平、垂直和对角三个方向的高频细节图像进行滤波;最后对增强处理后的低频近似图像与三个旋转核滤波后的高频细节图像进行线性增强,再对其进行重构,得到去噪后的图像。所提算法对于大脑等复杂组织的血管造影截面图像和在不同深度的切片层析图像,能够有效降低PT-OCT图像血管间的散斑噪声,比经典的RKT算法的方均根误差平均降低27.16,平均峰值信噪比提高3.68dB,从而提高血管造影的质量。
Abstract
In view of the different types of speckle noise in the photothermal optical coherence tomography (PT-OCT) three-dimensional image, an improved rotating kernel algorithm is used to suppress them. First, the PT-OCT images are decomposed by wavelet, and four sub-images with different frequency bands are obtained. Then, the foreground and background of the low-frequency approximation sub-images are separated by the maximum between-class variance algorithm, and the segmented enhancement is performed. The improved RKT algorithm is used to filter the high frequency detailed images in horizontal, vertical and diagonal directions respectively. Finally, the low frequency approximate image and the high frequency detail image after three rotating core filtering are linearly enhanced, and then reconstructed to obtain the de-noised image. The proposed algorithm can effectively reduce the speckle noise between vessels in PT-OCT images for angiographic cross section images of brain and other complex tissues and section tomography images at different depths. Compared with the classical RKT algorithm, the square-root mean error is reduced by 27.16 on average, and the average peak signal-to-noise ratio is increased by 3.68dB, which can improve the quality of angiography imaging.
黄伟源, 吴家怡, 任汉宏, 吴南寿, 魏波, 唐志列. 光热光学相干层析成像中基于小波变换的旋转核变换去噪算法[J]. 激光与光电子学进展, 2020, 57(22): 221005. 黄伟源, 吴家怡, 任汉宏, 吴南寿, 魏波, 唐志列. Rotating Kernel Transformation Denoising Algorithm Based on Wavelet Transform in Photothermal Optical Coherence Tomography[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221005.