基于传像光纤成像的蜂窝效应伪影修复算法

Restoration Algorithm for Honeycomb Artifacts Based on Optical Fiber Imaging

针对光纤传像束成像系统采集图像中存在的蜂窝效应伪影,通过分析蜂窝效应伪影产生机理及其相关特性,提出一种能够有效修复蜂窝效应伪影的方法。根据蜂窝效应伪影在图像中的分布特点,使用拆分法将原图拆分成多个子图,减小蜂窝效应伪影在图像中的宽度。然后使用一定大小的滑动窗口修复蜂窝效应伪影,在滑动窗口内,根据设计的自适应阈值机制,筛选出位于蜂窝效应伪影区域的像元,并计算该像元与窗口内像素值最大像元的像素值差值及欧氏距离,进而得到自适应补偿系数修复该像元,以滑动窗口遍历子图像完成对子图的全局修复。最后利用修复后的各子图完成重构,恢复成原始图像的尺寸。实验结果表明,与多种蜂窝效应伪影修复算法相比,所提方法在客观评价指标上有更好的表现,能更好地修复图像中的蜂窝效应伪影。

This study proposes an effective method for repairing honeycomb artifacts by analyzing generational mechanisms and the related characteristics of these honeycomb artifacts based on the honeycomb artifacts in images collected using a fiber bundle imaging system.According to the distribution characteristics of honeycomb artifacts in the image,the original image was first divided into several sub-images by a splitting method to reduce the honeycomb artifact’s image width.Then,a sliding window with a certain size was used to repair the honeycomb artifacts.Subsequently,the pixels located in the area of honeycomb artifacts were screened out of the sliding window according to the designed adaptive threshold mechanism,after which we calculated the pixel value difference and Euclidean distance between the pixel and another with the largest pixel value in the window to obtain the adaptive compensation coefficient for pixel repair,leading to a transverse of the sliding window and repair of the whole sub-image.Hence,an original image was finally formed with restored sub-images and vice versa.Based on the test results,the proposed method has a better performance,as shown by the objective evaluation index,indicating that it will repair the honeycomb artifacts in images better than the previously established honeycomb artifact restoration algorithms.