Li Hui, Yu Yi, Peng Jing, Wu Yuntao, Zhang Yanduo
School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
Hubei Key Laboratory of Intelligent Robot, Wuhan 430205, China.
Sensors (Basel). 2020 Sep 28;20(19):5557. doi: 10.3390/s20195557.
A relatively simple method to improve the image resolution of light field based on a liquid crystal (LC) microlens doped with multi-walled carbon nanotubes (MWCNTs) was developed and evaluated. As the nanoparticles were doped in LC, its electro-optical features could enhance, leading to a short response time compared to the pure LC microlens. With the maximum use of the proposed LC microlens, a method combining aperiodicity extraction and weighted average algorithm was adopted to realize the high-resolution light field imaging. The aperiodicity extraction method was proposed, which could effectively improve resolution of view angle image. For synthesizing the full resolution image at 0 Vrms and the extracted view angle image of light field imaging at 2.0 Vrms, the final high-resolution light field imaging could be obtained in a short time by weighted average algorithm. In this way, the common problem of low resolution in light field imaging could be solved. This proposed method was in good agreement with our experimental results. And it was also in line with the development of the trend of the smart imaging sensor combining algorithm with hardware.
开发并评估了一种基于掺杂多壁碳纳米管（MWCNT）的液晶（LC）微透镜来提高光场图像分辨率的相对简单的方法。由于纳米颗粒被掺杂到液晶中，其电光特性得以增强，与纯液晶微透镜相比，响应时间更短。为了最大程度地利用所提出的液晶微透镜，采用了一种结合非周期性提取和加权平均算法的方法来实现高分辨率光场成像。提出了非周期性提取方法，该方法可以有效提高视角图像的分辨率。对于合成0 Vrms时的全分辨率图像和2.0 Vrms时光场成像的提取视角图像，通过加权平均算法可以在短时间内获得最终的高分辨率光场成像。通过这种方式，可以解决光场成像中分辨率低的常见问题。所提出的方法与我们的实验结果高度吻合。并且它也符合算法与硬件相结合的智能成像传感器的发展趋势。
