Search Results (157)

Long-wave infrared (LWIR) airborne optical systems for ground imaging are widely utilized in applications such as ground reconnaissance, agricultural monitoring, counterterrorism, and other fields. Traditional oblique-view ground-imaging optical systems suffer from a critical drawback compared to nadir-view systems: the significant variation in object distances between distant and nearby targets. This disparity leads to inconsistent ground resolution (GR), manifesting in images where distant targets exhibit significantly lower resolution than nearby ones. This characteristic is highly detrimental to information acquisition and three-dimensional modeling of the system. Furthermore, the limited field of view of fixed focal length systems prevents the unmanned aerial vehicle (UAV) from acquiring target information effectively across varying flight altitudes. To address this issue, this paper designs an oblique imaging optical system capable of achieving both constant GR and zoom functionality in the LWIR band. By controlling the ground resolution, a LWIR continuous zoom optical system was designed. The system maintains constant GR over the entire field of view. Its modulation transfer function (MTF) approaches the diffraction limit across the full field of view, and the spot diagram remains within Airy’s disk at each view angle. The radius of the spot diagram is smaller than that of the Airy disk, indicating that the geometric aberrations of the system are well corrected. The imaging performance is primarily determined by the wavelength and the F-number. In the case of LWIR, the longer wavelength results in a larger Airy disk radius. The system meets imaging quality requirements and is suitable for air-to-ground target reconnaissance imaging. Full article

Carbon fibre reinforced polymers (CFRPs) are increasingly used in biomedical and safety-critical applications, where embedded and real-time non-destructive testing (NDT) is essential to ensure structural integrity. This paper presents a cost-effective, AI-assisted thermographic inspection system designed from an embedded electronics and circuit-level perspective. The proposed platform integrates a long-wave infrared (LWIR) sensor, dedicated signal conditioning and power management circuits, and a Raspberry Pi-based processing unit within a unified hardware–software co-design approach. Infrared data acquired under surface heating conditions are processed on-board using a convolutional neural network based on a U-Net architecture, enabling automatic localisation and classification of subsurface defects in CFRP samples. Particular attention is devoted to embedded design constraints, including sensor interfacing, acquisition timing, end-to-end latency, and real-time processing scalability. Experimental results confirm the feasibility of real-time surface heat assessment and the robustness of the proposed architecture in detecting delaminations and voids. The presented system contributes to the development of intelligent embedded inspection electronics and provides a reference design for edge AI-enabled NDT systems in industrial and biomedical applications. Full article

This study proposes a dual-band, mid-wave infrared (MWIR) and long-wave infrared (LWIR) polarization-multiplexed optical system based on a metasurface. By employing matrix-based phase encoding technology, we pioneered the use of a dual-band polarization multiplexing architecture for parallel processing, achieving full-Stokes polarization detection. This system realized wavelength and polarization multiplexing across six axial focal planes and the off-axis focal points on each focal plane. The system also achieved a high transmittance of 85%; the average transmittance of this system exceeded 70% in the 3–12 μm range. The focusing efficiency in the MWIR and LWIR is 71.1% and 62.5%, respectively, with polarization crosstalk below −25 dB. We used the inverse design method, shortening the design cycle by 80%. It provides a compact solution for infrared imaging, multispectral analysis, and biological tissue pathological detection. Full article

Hyperspectral imaging in the long-wave infrared (LWIR) range enables identification of chemical compositions and material properties, but reconstructing 3D models from gimballed pushbroom sensors remains challenging because their unique acquisition geometry is incompatible with conventional photogrammetric software designed for frame cameras. This study presents a workflow for creating explorable 3D models from multi-angle LWIR hyperspectral imagery by co-registering hyperspectral line-scan data with simultaneously acquired RGB frame camera imagery using deep learning-based image matching. The co-registered images are processed in commercial photogrammetric software (Agisoft Metashape), and a texture-to-image mapping algorithm preserves correspondences between 3D model coordinates and original hyperspectral pixels across multiple viewing angles. Quantitative evaluation against reference data demonstrates that co-registration reduces geometric error approaching the accuracy of models built from high-resolution RGB imagery. The resulting models enable the retrieval of 8–50 spectral signatures per surface point, captured from different viewing geometries. This approach facilitates interactive exploration of angular variations in thermal infrared spectra, supporting material identification for non-Lambertian surfaces where single-angle observations may be insufficient for reliable classification. Full article

Multispectral infrared imaging systems that simultaneously operate in the long-wave infrared (LWIR) and mid-wave infrared (MWIR) bands offer significant advantages for target detection and recognition. However, conventional infrared optical systems rely on bulky multi-element lens assemblies to accommodate incident wavelengths of LWIR and MWIR bands, making it challenging for compact thermal optics design. Here, we propose and experimentally demonstrate an inverse designed infrared metalens capable of simultaneously focusing LWIR and MWIR radiation at wavelengths of 9.5 μm and 4.75 μm with a focal length variation of 1%. In the experiment, the proposed metalens with detector enables a dual-wavelength thermal imaging with a compact size (26 × 26 × 18 mm³) and a light weight (19 g). This work establishes a robust and scalable inverse design strategy for dual-wavelength infrared metalenses and provides a promising route toward compact, integrated, and multifunctional infrared imaging lens. Full article

A decrease in conductivity under illumination, known as negative photoconductivity, has been observed in various semiconductors and is commonly attributed to trapping of excess carriers by deep centers. Here, we demonstrate that negative photoconductivity can instead arise from a rapid increase in carrier scattering in ultranarrow-gap semiconductors with degenerate carrier statistics. This behavior is explained by the combined effects of enhanced optical phonon emission scattering and an increase in effective mass due to band filling. Experimentally, photoconductivity was measured over wide ranges of excitation and temperature in unintentionally doped n-type short-period InAsSb_0.6/InAsSb_0.3 strained-layer superlattices (SLS), relevant for long-wavelength infrared optoelectronic devices. The resistive device impedance, weakly dependent on excess carrier concentration, simplifies broadband impedance matching to low-voltage CMOS driver electronics. At 77 K, 10.6 µm laser excitation led to an initial rise in conductivity, with a decrease observed above 10 W/cm². Full article

This study presents a measurement–modeling pathway for diagnosing corrosion-driven contact degradation in power equipment using infrared thermography and color-channel analysis. Thermal data were acquired with a Fluke Ti450 (LWIR, 7.5–14 μm) under typical high-altitude, temperate conditions in Quito, Ecuador. Radiometric parameters (emissivity, distance, ambient/reflected temperature, and humidity) are reported explicitly, and images are processed with a reproducible pipeline that combines adaptive thresholding, morphology, and region-of-interest statistics, including $\Delta T$ relative to a reference region. A worked example links an observed hotspot to emissivity-corrected temperature and discusses qualitative implications for the effective contact resistance $R_{\mathrm{eff}}$. Uncertainty is summarized through a per-case template that propagates $u_{\Delta T}$ to $u\left(R_{\mathrm{eff}}\right)$ and Weibull characteristic life $\eta$. Environmental influences (solar load, wind, and emissivity variability) are acknowledged and mitigated. Two field cases illustrate the approach to substation assets. Because the dataset comprises single-visit inspections, formal parameter estimation (e.g., EIS-validated $R_{\mathrm{eff}}$ and full Weibull/Arrhenius fits) is reserved for longitudinal follow-up. By making radiometry, processing steps, and limitations explicit, the study reduces ambiguity in the transition from temperature contrast to physics-based interpretation and supports auditable maintenance decisions. Full article

Silicon windows in wafer-level packaged LWIR sensors suffer ~30% Fresnel reflection per interface, limiting optical throughput and detector sensitivity. We present an end-to-end design, fabrication, and validation framework for CMOS-compatible moth-eye anti-reflection coatings patterned directly on silicon wafers. Our approach integrates the effective medium theory, a transfer matrix analysis, full-wave FDTD simulations, and experimental Fourier-transform infrared (FTIR) measurements to optimize subwavelength pillar arrays for broadband (8–14 μm) and angle-tolerant performance. Fabricated structures demonstrate a 46.7% responsivity boost in CMOS–SOI–MEMS thermal sensors compared to bare silicon windows, while simulations predict up to 85.1% transmission and 57.1% responsivity enhancement for double-sided patterning. These results establish moth-eye metasurfaces as a scalable, CMOS-compatible solution for next-generation wafer-level processing and packaging infrared sensing platforms, transforming optical improvements into measurable electrical performance gains. The contribution of this work is the end-to-end framework for designing moth-eye wafer level processing and packaging for “real-life” CMOS-compatible infrared sensors manufacturing. Full article

The photovoltaic (PV) bands on the mid-wave and long-wave infrared (MWIR and LWIR) cold focal plane assemblies of Terra and Aqua MODIS have suffered from gradually increasing electronic crosstalk contamination as both instruments have continued to operate in their extended missions, respectively. This contamination has considerable impact, particularly for the PV LWIR bands, which includes image striping and radiometric bias in the Level-1B (L1B)-calibrated radiance products as well as higher level (and mostly atmospheric but also land and oceanic) products (e.g., cloud phase particle, cloud mask, land and sea surface temperatures). The crosstalk was characterized early in the mission, and test corrections were developed then. Ultimately, the groundwork for a robust electronic crosstalk correction algorithm was developed in 2016 and implemented in MODIS Collection 6.1 (C6.1) back in 2017 for the Terra MODIS PV LWIR bands. It was later introduced in Aqua MODIS C6.1 for the same group of bands in April 2022. Additional improvements were made in MODIS Collection 7 (C7) to better characterize the electronic crosstalk in the PV LWIR bands, and the electronic crosstalk correction algorithm was also extended to select detectors in the MODIS MWIR bands. This work will describe the electronic crosstalk correction algorithm and its application on the MODIS L1B product, the differences in application between C6.1 and C7, as well as additional improvements made to enhance the contamination correction and improve image quality for the Aqua MODIS PV LWIR bands. The electronic crosstalk correction coefficient time series for the MODIS PV bands will be discussed, and some cases will be presented to illustrate how image quality improves on the L1B and Level 2 products after the correction is applied. Lastly, experiences gained regarding the PV bands electronic crosstalk and the strategy used to correct it will be discussed to provide future data users and scientists with an insight as to how to improve on the legacy record that the Terra and Aqua MODIS sensors will leave behind after both spacecrafts are decommissioned. Full article

We present, for the first time, a design and measured data for a meanderline reflective quarter-wave plate suitable for operation in the 3- to 5-micron MWIR band. Across this spectral range, the reflection coefficient is around 80%, the axial ratio is less than 2, and the polarization conversion ratio is above 75%. We also demonstrate experimentally that the meanderline structure has stable performance as a reflective quarter-wave plate over a 20-degree angular bandwidth centered around incident angles between 35 and 55 degrees. One notable difference as compared to LWIR meanderline waveplates is that the vertical height of the grid lines is necessarily larger, to keep the relative phase between TE and TM near 90°. Full article

Real-time monitoring of hazardous gas emissions in open environments remains a critical challenge. Conventional spectrometers and filter wheel systems acquire spectral and spatial information sequentially, which limits their ability to capture multiple gas species and dynamic dispersion patterns rapidly. A High-Resolution Snapshot Multispectral Imaging System (HRSMIS) is proposed to integrate high spatial fidelity with multispectral capability for near real-time plume visualization, gas species identification, and concentration retrieval. Operating across the 7–14 $\mathsf{\mu }$m spectral range, the system employs a dual-path optical configuration in which a high-resolution imaging path and a multispectral snapshot path share a common telescope, allowing for the simultaneous acquisition of fine two-dimensional spatial morphology and comprehensive spectral fingerprint information. Within the multispectral path, two $5\times 5$ microlens arrays (MLAs) combined with a corresponding narrowband filter array generate 25 distinct spectral channels, allowing concurrent detection of up to 25 gas species in a single snapshot. The high-resolution imaging path provides detailed spatial information, facilitating spatio-spectral super-resolution fusion for multispectral data without complex image registration. The HRSMIS demonstrates modulation transfer function (MTF) values of at least 0.40 in the high-resolution channel and 0.29 in the multispectral channel. Monte Carlo tolerance analysis confirms imaging stability, enabling the real-time visualization of gas plumes and the accurate quantification of dispersion dynamics and temporal concentration variations. Full article

Predicting internal quality parameters, such as Brix and water content, of apples, is essential for quality control. Existing near-infrared (NIR) and hyperspectral imaging (HSI)-based techniques have limited applicability due to their dependence on equipment and environmental sensitivity. In this study, a transportable quality assessment system was proposed using spatiotemporal domain analysis with long-wave infrared (LWIR)-based thermal diffusion phenomics, enabling non-destructive prediction of the internal Brix of apples during transport. After cooling, the thermal gradient of the apple surface during the cooling-to-equilibrium interval was extracted. This gradient was used as an input variable for multiple linear regression, Ridge, and Lasso models, and the prediction performance was assessed. Overall, 492 specimens of 5 cultivars of apple (Hongro, Arisoo, Sinano Gold, Stored Fuji, and Fuji) were included in the experiment. The thermal diffusion response of each specimen was imaged at a sampling frequency of 8.9 Hz using LWIR-based thermal imaging, and the temperature changes over time were compared. In cross-validation of the integrated model for all cultivars, the coefficient of determination (R²_cv) was 0.80, and the RMSEcv was 0.86 °Brix, demonstrating stable prediction accuracy within ±1 °Brix. In terms of cultivar, Arisoo (Cultivar 2) and Fuji (Cultivar 5) showed high prediction reliability (R²_cv = 0.74–0.77), while Hongro (Cultivar 1) and Stored Fuji (Cultivar 4) showed relatively weak correlations. This is thought to be due to differences in thermal diffusion characteristics between cultivars, depending on their tissue density and water content. The LWIR-based thermal diffusion analysis presented in this study is less sensitive to changes in reflectance and illuminance compared to conventional NIR and visible light spectrophotometry, as it enables real-time measurements during transport without requiring a separate light source. Surface heat distribution phenomics due to external heat sources serves as an index that proximally reflects changes in the internal Brix of apples. Later, this could be developed into a reliable commercial screening system to obtain extensive data accounting for diversity between cultivars and to elucidate the effects of interference using external environmental factors. Full article

Accurate modelling of reflection, transmission, absorption, and emission at material interfaces is essential for infrared imaging, rendering, and the simulation of optical and sensing systems. This need is particularly pronounced across the short-wave to long-wave infrared (SWIR–LWIR) spectrum, where many materials exhibit dispersion- and wavelength-dependent attenuation described by complex refractive indices. In this work, we introduce a unified formulation of the full Fresnel equations that directly incorporates wavelength-dependent complex refractive-index data and provides physically consistent interface behaviour for both dielectrics and conductors. The approach reformulates the classical Fresnel expressions to eliminate sign ambiguities and numerical instabilities, resulting in a stable evaluation across incidence angles and for strongly absorbing materials. We demonstrate the model through spectral-rendering simulations that illustrate realistic reflectance and transmittance behaviour for materials with different infrared optical properties. To assess its suitability for thermal-infrared applications, we also compare the simulated long-wave emission of a heated glass sphere with measurements from a LWIR camera. The agreement between measured and simulated radiometric trends indicates that the proposed formulation offers a practical and physically grounded tool for wavelength-parametric interface modelling in infrared imaging, supporting applications in spectral rendering, synthetic data generation, and infrared system analysis. Full article

We present an inverse designed metalens for long-wave infrared (LWIR) imaging tailored to consumer and Internet of Things (IoT) platforms. Conventional LWIR optics either rely on costly specialty materials or suffer from low efficiency and narrow fields of view (FoV), limiting scalability. Our approach integrates adjoint-based inverse design with fabrication-aware constraints and a cone-shaped source model that efficiently captures oblique incidence during optimization. The resulting multi-level metalens achieves a wide FoV up to 100° while maintaining robust focusing efficiency and stable angle-to-position mapping on low-power $4\times 4$ microbolometer arrays representative of edge devices. We further demonstrate application-level imaging on $4\times 4$ microbolometer arrays, showing that the proposed metalens delivers a substantially wider FoV than a commercial narrow FoV lens while meeting low-resolution, low-cost, and low-power constraints for edge LWIR modules. By eliminating bulky multi-element stacks and reducing cost and form factor, the proposed design provides a practical pathway to compact, energy-efficient LWIR modules for consumer applications such as occupancy analytics, smart-building automation, mobile sensing, and outdoor fire surveillance. Full article

This paper presents a cascaded imaging method that combines low-light enhancement and visible–long-wavelength infrared (VIS-LWIR) image fusion to mitigate image degradation in dark environments. The framework incorporates a Low-Light Enhancer Network (LLENet) for improving visible image illumination and a heterogeneous information fusion subnetwork (IXNet) for integrating features from enhanced VIS and LWIR images. Using a joint training strategy with a customized loss function, the approach effectively preserves salient targets and texture details. Experimental results on the LLVIP, M³FD, TNO, and MSRS datasets demonstrate that the method produces high-quality fused images with superior performance evaluated by quantitative metrics. It also exhibits excellent generalization ability, maintains a compact model size with low computational complexity, and significantly enhances performance in high-level visual tasks like object detection, particularly in challenging low-light scenarios. Full article