小波变换和分数阶积分结合的OCT图像去噪算法  

Optical Coherence Tomography Image Denoising Algorithm Based on Wavelet Transform and Fractional Integral

作　　者：张晨曦 陈明惠[1] 王帆 高乃珺 郑刚[1] Zhang Chenxi;Chen Minghui;Wang Fan;Gao Naijun;Zheng Gang(School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology,Shanghai 200093, China)

机构地区：[1]上海理工大学医疗器械与食品学院

出　　处：《激光与光电子学进展》2019年第18期153-161,共9页Laser & Optoelectronics Progress

基　　金：国家自然科学基金青年科学基金(6130115);上海市自然科学基金(13ZR1457900);上海市科委产学研医项目(15DZ1940400)

摘　　要：通过对光学相干层析(OCT)系统中的噪声源进行分析,提出了一种将小波变换和分数阶积分结合的OCT图像去噪方法。先将OCT图像进行小波分解,获得不同频带的子图像。将低频近似图像保持不变,对水平、垂直和对角三个方向的高频细节图像采用三种改进的分数阶积分Tiansi模板进行滤波,最后将低频近似图像与三个分数阶积分滤波后的高频细节图像合成,得到去噪后的图像。实验结果表明;该算法在有效降低OCT图像散斑噪声的同时,尽可能地保留了图像的细节;相比经典的去噪算法和单一的分数阶积分算法,本文算法的去噪效果较好。Optical coherence tomography (OCT) is affected by speckle noise, which affects the analysis of the OCT images and their diagnostic utility. Herein, we propose an OCT image denoising method based on the wavelet transform and fractional integral by analyzing the noise sources in the OCT system. First, the OCT image is decomposed into various frequency sub-band images via the wavelet transform. Further, the high-frequency subband images are filtered in the horizontal, vertical, and angular directions using three improved fractional integral Tiansi templates without changing the low-frequency approximation image. Finally, the denoised image is obtained by composing three high-frequency detail images with fractional integral filtering and the low-frequency approximation image. The experimental results demonstrate that the proposed algorithm can effectively reduce the speckle noise in OCT images while maintaining the detail in the image;the proposed method exhibits a better denoising effect than the classical filtering methods and the single fractional integral algorithm.

关 键 词：图像处理 光学相干层析成像 散斑噪声 小波变换 分数阶积分 图像去噪 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]