Han Bin, Zhao Quanchao, Shi Moudan, Wang Kexin, Shen Yunan, Cao Jie, Hao Qun
School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China.
Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314019, China.
Biomimetics (Basel). 2024 Dec 18;9(12):768. doi: 10.3390/biomimetics9120768.
This study presents a cutting-edge imaging technique for special unmanned vehicles (UAVs) designed to enhance tunnel inspection capabilities. This technique integrates ghost imaging inspired by the human visual system with lateral inhibition and variable resolution to improve environmental perception in challenging conditions, such as poor lighting and dust. By emulating the high-resolution foveal vision of the human eye, this method significantly enhances the efficiency and quality of image reconstruction for fine targets within the region of interest (ROI). This method utilizes non-uniform speckle patterns coupled with lateral inhibition to augment optical nonlinearity, leading to superior image quality and contrast. Lateral inhibition effectively suppresses background noise, thereby improving the imaging efficiency and substantially increasing the signal-to-noise ratio (SNR) in noisy environments. Extensive indoor experiments and field tests in actual tunnel settings validated the performance of this method. Variable-resolution sampling reduced the number of samples required by 50%, enhancing the reconstruction efficiency without compromising image quality. Field tests demonstrated the system's ability to successfully image fine targets, such as cables, under dim and dusty conditions, achieving SNRs from 13.5 dB at 10% sampling to 27.7 dB at full sampling. The results underscore the potential of this technique for enhancing environmental perception in special unmanned vehicles, especially in GPS-denied environments with poor lighting and dust.
本研究提出了一种用于特殊无人机（UAV）的前沿成像技术，旨在增强隧道检测能力。该技术将受人类视觉系统启发的鬼成像与侧向抑制和可变分辨率相结合，以改善在诸如光线不足和多尘等具有挑战性条件下的环境感知。通过模拟人眼的高分辨率中央凹视觉，该方法显著提高了感兴趣区域（ROI）内精细目标的图像重建效率和质量。该方法利用非均匀散斑图案与侧向抑制相结合来增强光学非线性，从而获得卓越的图像质量和对比度。侧向抑制有效抑制背景噪声，从而提高成像效率，并在嘈杂环境中大幅提高信噪比（SNR）。在实际隧道环境中的大量室内实验和现场测试验证了该方法的性能。可变分辨率采样将所需样本数量减少了50%，在不影响图像质量的情况下提高了重建效率。现场测试表明，该系统能够在昏暗和多尘条件下成功对诸如电缆等精细目标成像，采样率为10%时信噪比为13.5 dB，全采样时为27.7 dB。结果强调了该技术在增强特殊无人机环境感知方面的潜力，特别是在光照不足和多尘的无GPS环境中。
