As one of the most promising schemes to address the bottleneck confronted by conventional optical devices (e.g., bulky sizes, high cost, and complex geometrical structure), metalens have drawn great attentions in the recent years. In this work, a metalens operating in mid-wave infrared (MW-IR) range is proposed, which can accomplish broadband achromatic under both x- and y-polarization incidence. In order to satisfy the strict phase requirements with relatively high transmission, three types of architectures composed of silicon symmetrical structures on a hexagonal magnesium fluoride substrate are delicately designed. In specific, these meta-atoms are supposed to simultaneously realize MW-IR waves focusing at 4.2 μm, and they can also compensate the phase differences between 3.7 to 4.2 μm. The numerical results indicate that the chromatic aberration in the concerned wavelength range can be well corrected for both x- and y-polarized incidence, and the corresponding maximum deviation values of focal length are only 3.10% and 3.09%, respectively. Moreover, the average focusing efficiencies of two different incidences are 51.15% and 49.01%, respectively. This work may have great potential to promote the integration of broadband MW-IR devices.
Spectral imaging technology based on on-chip splitting provides services for aerospace, industrial and consumer electronics applications. Since each application requires a different set and number of spectral bands, the lack of scalable and high-cost customized splitting schemes hinders the wide application of multispectral imaging. Here, we demonstrate a compact, highly freely customizable imaging spectrometer with initial validation for coal and gangue classification and recognition applications. And the results reflect the potential application of this spectral imaging system in coal and gangue classification and identification. A supervised classification method using support vector machines (SVM) was used to recognize coal and gangue, and the evaluation of classification accuracy shows that more than 82% of the pixels can be correctly classified, and this study provides strong support for the visual sensors with complete spectral band combinations to achieve higher accuracy.
In this study, we introduce a novel approach for achieving narrowband filters in hyperspectral imaging spectrometers. By embedding photonic crystals within distributed Bragg reflectors (DBRs), we create resonant structures. Through meticulous simulations, we optimize a four-layer DBR configuration, resulting in spectral channels with a 3 nm average FWHM and exceeding 99% peak transmittance. Our key innovation lies in using photonic crystals to modulate transmission. By introducing TiO2 periodic structures, we control the effective refractive index and there by tune transmission wavelengths. The method covers a 475-625 nm spectral range with exceptional transmittance. We also investigate incident light angle effects, revealing systematic shifts in transmission peak. Our design offers adaptability by adjusting DBR film thickness for defining operational ranges and selecting TiO2 cylinder radii for precise channel manipulation. Our approach simplifies fabrication and holds potential for cost-effective hyperspectral imaging filters.
In the field of face anti-counterfeiting, there are differences between the reflection spectrum of real faces and simulated faces, which can help us overcome the shortcomings of traditional RGB cameras that are difficult to identify the authenticity of faces. In our work, we designed a face anti-spoofing imaging system based on the snapshot spectral imaging chip, which can be used in face anti-spoofing imaging through the analysis of spectral imaging data. Experiments show that our sensor could reconstruct the spectrum of the face region, establish the spectral databases, and achieve face authenticity recognition under active light source based on deep convolutional neural network, with a face recognition accuracy of 95%.
KEYWORDS: Biomimetics, Cameras, Calibration, Distance measurement, 3D acquisition, 3D image processing, Eye, 3D vision, Target detection, Imaging systems
In the bionic curved compound-eye camera (BCCEC) we have invented, the overlapping field of view (FOV) among the ommatidia makes 3D detection possible. In this work, we analyzed the overlapping FOV in BCCEC in detail to prove its potential in 3D detection and designed a new experiment to test its performance. In that the FOVs of multiple ommatidia in BCCEC overlap each other, the FOV of a single ommatidium is used as a representative analysis. The relationship between the overlapping ratio of FOV and the object distance is quantitatively calculated. The results show that more than 95% of the FOV can be 3D reconstructed when the object distance exceeds 32 cm. Next, in order to realize the automatic calibration of all ommatidia, ommatidia are numbered and an addressing algorithm based on the number information of ommatidia is designed, which can be used to determine the adjacent ommatidia of any ommatidium so as to acquire the ommatidia pairs that need to be calibrated. Then, since the aperture of ommatidium is relatively small and it is difficult to accurately align, a new 3D detection experiment is designed. The laser rangefinder is fixed, the black paper is used to block the laser and the formed light spot is used as the detection target. The experimental results show that 3D detection can be performed in the whole FOV of BCCEC. The BCCEC can obtain multi-dimensional information in a large FOV, and it have greater application potential in obstacle avoidance and navigation.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.