结肠镜检查视频帧中的自适应镜面反射检测和修复
Adaptive specular reflection detection and inpainting in colonoscopy video frames
摘要：
结肠镜检查视频帧可能被具有不饱和值（称为镜面反射）的亮点污染。检测和消除这些反射可以提高结肠镜图像的质量，并有助于诊断过程。在本文中，我们提出了一种新的两阶段的方法，包括检测和删除阶段。在检测阶段，我们采用HSV和RGB颜色空间的信息分割镜面反射。我们首先训练一个非线性支持向量机选择颜色空间的基础上，从每个通道的颜色空间中提取的图像统计特征。然后，引入了用于检测镜面反射的成本函数。在去除阶段，我们提出了一个两步修复方法，其中包括适当的替换补丁选择和块效应的去除。该方法通过在结肠镜图像数据库上的测试进行了评估，准确率和Dice评分分别达到99.68%和71.79%。
英文摘要：
Colonoscopy video frames might be contaminated by bright spots with unsaturated values known as specular reflection. Detection and removal of such reflections could enhance the quality of colonoscopy images and facilitate diagnosis procedure. In this paper we propose a novel two-phase method for this purpose, consisting of detection and removal phases. In the detection phase, we employ both HSV and RGB color space information for segmentation of specular reflections. We first train a non-linear SVM for selecting a color space based on image statistical features extracted from each channel of the color spaces. Then, a cost function for detection of specular reflections is introduced. In the removal phase, we propose a two-step inpainting method which consists of appropriate replacement patch selection and removal of the blockiness effects. The proposed method is evaluated by testing on an available colonoscopy image database where accuracy and Dice score of 99.68% and 71.79% are achieved respectively.
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