Zhou Sheng, Goodliffe Jim, Cai Hao, Zhou Kui, Zhang Xianglin
Appl Opt. 2014 Aug 10;53(23):5205-10. doi: 10.1364/AO.53.005205.
An optical imaging signal is vulnerable to undesired features such as ambient light illumination and partial specular reflection from the target; the success of extracting target features from images depends largely on appropriate design of illumination. This paper presents an approach for self-adaptive illumination for optical imaging systems. The proposed illumination system projects a reference image to a target surface as an initial structured illumination, and then adjusts the projected image automatically to compensate the negative influences of undesired features. After this self-adaptive control process, undesired features would appear mostly invisible in the captured images. The signal-to-noise ratio would be improved dramatically well before subsequent image processing. In the validation experiments, several images with uniform brightness were offered as reference images; the captured images could achieve high brightness uniformity, even when the target surface was uneven or was illuminated by ambient light. In a further experiment of selective vessel illumination on a human palm, simulated vessel regions were selectively illuminated. Undesired features, like palm prints, almost disappeared in the images captured.
光学成像信号容易受到诸如环境光照和目标的部分镜面反射等不良特征的影响；从图像中提取目标特征的成功很大程度上取决于照明的适当设计。本文提出了一种用于光学成像系统的自适应照明方法。所提出的照明系统将参考图像投影到目标表面作为初始结构化照明，然后自动调整投影图像以补偿不良特征的负面影响。经过这种自适应控制过程后，不良特征在捕获的图像中大多会变得不可见。在后续图像处理之前，信噪比将得到显著提高。在验证实验中，提供了几张亮度均匀的图像作为参考图像；即使目标表面不平或受到环境光照射，捕获的图像也能实现高亮度均匀性。在对人手掌进行选择性血管照明的进一步实验中，模拟血管区域被选择性照明。诸如掌纹等不良特征在捕获的图像中几乎消失。
