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High Dynamic Range (HDR) virtual bronchoscopy rendering for video tracking

机译:高动态范围(HDR)虚拟支气管镜渲染,用于视频跟踪

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摘要

In this paper, we present the design and implementation of a new rendering method based on high dynamic range (HDR) lighting and exposure control. This rendering method is applied to create video images for a 3D virtual bronchoscopy system. One of the main optical parameters of a bronchoscope's camera is the sensor exposure. The exposure adjustment is needed since the dynamic range of most digital video cameras is narrower than the high dynamic range of real scenes. The dynamic range of a camera is defined as the ratio of the brightest point of an image to the darkest point of the same image where details are present. In a video camera exposure is controlled by shutter speed and the lens aperture. To create the virtual bronchoscopic images, we first rendered a raw image in absolute units (luminance); then, we simulated exposure by mapping the computed values to the values appropriate for video-acquired images using a tone mapping operator. We generated several images with HDR and others with low dynamic range (LDR), and then compared their quality by applying them to a 2D/3D video-based tracking system. We conclude that images with HDR are closer to real bronchoscopy images than those with LDR, and thus, that HDR lighting can improve the accuracy of image-based tracking.
机译:在本文中,我们介绍了一种基于高动态范围(HDR)照明和曝光控制的新渲染方法的设计和实现。该渲染方法适用于为3D虚拟支气管镜系统创建视频图像。支气管镜相机的主要光学参数之一是传感器曝光。由于大多数数码摄像机的动态范围都比真实场景的高动态范围窄,因此需要进行曝光调整。摄像机的动态范围定义为存在细节的图像的最亮点与同一图像的最暗点之比。在摄像机中,曝光是由快门速度和镜头光圈控制的。要创建虚拟支气管镜图像,我们首先以绝对单位(亮度)渲染原始图像。然后,我们通过使用色调映射运算符将计算值映射到适合视频获取图像的值来模拟曝光。我们用HDR和低动态范围(LDR)生成了几张图像,然后将它们应用于基于2D / 3D视频的跟踪系统,从而比较了它们的质量。我们得出的结论是,具有HDR的图像比具有LDR的图像更接近真实的支气管镜图像,因此,HDR照明可以提高基于图像的跟踪的准确性。

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