For conventional camera calibration methods, well-focused images are necessary to detect features accurately. However, this requirement causes practical inconveniences to image acquisition for long- and short-distance photogrammetry. In this study, three active phase-shift circular grating (PCG) arrays are used as calibration patterns. The PCGs’ centers are regarded as feature points that can be accurately extracted by ellipse fitting of $2\pi$-phase points even though patterns are substantially blurred. In the experiments, Gaussian filters are utilized to blur pattern images, and different standard deviations are set for different fuzzy degrees. Pattern images with different defocusing degrees are also captured. The period and number of PCGs and noise are considered. Experimental results indicate that our method is accurate, reliable, and insensitive to image defocusing.

A compound eye has the advantages of a large field of view, high sensitivity, and compact structure, showing that it can be applicable for 3D object detection. In this work, an artificial compound eye system is developed for 3D object detection, consisting of a layer of lenslets and a prism-like beam-steering lens. A calibration method is developed for this system, with which the correspondences between incident light rays and the relevant image points can be obtained precisely using an active calibration pattern at multiple positions. Theoretically, calibration patterns at two positions are sufficient for system calibration, although more positions will increase the accuracy of the result. 3D positions of point objects are calculated to evaluate the system, which are obtained by the intersection of multiple incident light rays in the least-squares sense. Experimental results show that the system can detect an object with angular accuracy of better than 1 mrad, demonstrating the feasibility of the proposed compound eye system. With a 2D scanning device, the system can be extended for general object detection in 3D space.

An aspherical lens is fabricated from an ultraviolet (UV) curable polymer and is characterized by measuring its focal spot. Electrostatic force is employed to manipulate the shape of the liquid polymer lens. Experiment results show that a liquid lens in a strong electrostatic field can be distorted from initial spherical shape to parabolic to even near cone shape. With in situ measurement of the surface profile and focal spot, an aspherical liquid lens with good performance can be cured to a solid aspherical lens by UV light. A probe scanning microscope is employed to accurately measure the focal spot of the aspherical lens, and the modulation transfer function (MTF) of the aspherical lens is calculated to characterize it. A focal spot of $1.825\mathrm{\mu m}$ diameter, an MTF of $800\text{\hspace{0.17em}line pair}\mathrm{s}/\mathrm{mm}$ cutoff spatial frequency, and a Strehl ratio of 0.742 are achieved. These demonstrate the feasibility of fabricating an aspherical lens with small aberrations by using this method.

The timely and accurate detection of unidentified drones is vital for public safety. However, the unique characteristics of drones in complex environments and the varied postures they may adopt during approach present significant challenges. Additionally, deep learning algorithms often require large models and substantial computational resources, limiting their use on low-capacity platforms. To address these challenges, we propose LAMS-YOLO, a lightweight drone detection method based on linear attention mechanisms and adaptive downsampling. The model’s lightweight design, inspired by CPU optimization, reduces parameters using depthwise separable convolutions and efficient activation functions. A novel linear attention mechanism, incorporating an LSTM-like gating system, enhances semantic extraction efficiency, improving detection performance in complex scenarios. Building on insights from dynamic convolution and multi-scale fusion, a new adaptive downsampling module is developed. This module efficiently compresses features while retaining critical information. Additionally, an improved bounding box loss function is introduced to enhance localization accuracy. Experimental results demonstrate that LAMS-YOLO outperforms YOLOv11n, achieving a 3.89% increase in mAP and a 9.35% reduction in parameters. The model also exhibits strong cross-dataset generalization, striking a balance between accuracy and efficiency. These advancements provide robust technical support for real-time drone monitoring.

Camera parameters can’t be estimated accurately using traditional calibration methods if the camera is substantially defocused. To tackle this problem, an improved approach based on three phase-shifting circular grating (PCG) arrays is proposed in this paper. Rather than encoding the feature points into the intensity, the proposed method encodes the feature points into the phase distribution, which can be recovered precisely using phase-shifting methods. The PCG centers are extracted as feature points, which can be located accurately even if the images are severely blurred. Unlike the previous method which just uses a single circle, the proposed method uses a concentric circle to estimate the PCG center, such that the center can be located precisely. This paper also presents a sorting algorithm for the detected feature points automatically. Experiments with both synthetic and real images were carried out to validate the performance of the method. And the results show that the superiority of PCG arrays compared with the concentric circle array even under severe defocus.

We propose and realize a packaged structure for the microcylinder–taper coupling system by only gluing a glass tube and two glass plates together. Our package method avoids embedding the coupling system into the polymer, thus leaving the whispering gallery mode evanescent fields available for environmental sensing. The excitation of localized high-order axial modes in the cylindrical resonator fabricated by using a fusion splicer is demonstrated and a quality factor ($Q$) up to $1.4\times {10}^7$ is obtained. The $Q$ maintenance and stable spectrum are realized by sealing the packaged device in a clean box. Moreover, the robustness of the packaged structure is also tested, demonstrating its remarkable antivibration ability. The portability and robustness of the device make it attractive in practical applications such as sensors, lasers, and especially some applied areas in strong vibration environments.