Search Results (40)

Infrared imaging has unique advantages in remote sensing observation and non-contact measurement, but its inherent low contrast and blurred structural details limit the reliability of scene interpretation by human observers. Unlike deep learning-based approaches that rely on data-driven training and substantial computational resources, we propose a Hybrid Prior Enhanced Decomposition (HPED) model, a training-free, model-driven framework that incorporates structural and luminance priors into a multi-stage enhancement pipeline. An l₁–l₀-regularized decomposition separates the input into a base layer that preserves global structures and salient edges and a detail layer in which low-amplitude fluctuations and noise are suppressed. A prior-preserving bi-gamma correction method enhances base-layer contrast through prior-guided histogram segmentation and adaptive gray-level redistribution. An improved grayscale mapping strategy further enhances global contrast while maintaining interframe consistency. Experiments on real SWIR, MWIR, and LWIR images show that HPED ranks first among evaluated traditional and deep learning-based methods on key perceptual quality metrics (SSIM, VIF, LIF), while achieving over 25 fps on a CPU-only platform, sufficient for smooth real-time visual display. Task-oriented evaluation further shows that the HPED improves CNR and SCR by 174.7 ± 11.4% and 298.5 ± 52.1% on average over the raw input, outperforming all competing methods and suggesting potential applicability in downstream machine perception tasks such as detection and tracking. Full article

Accurate spot-centroid localization is fundamental for determining optical metrics such as modulation transfer function (MTF) and effective focal length (EFL). Conventional methods struggle under non-ideal conditions—asymmetric spots, high noise, and vibration—and mid-wave infrared (MWIR) vibration has received little attention. To address these gaps, we propose multi-scale Gaussian fitting with subpixel edge reconstruction (MSGF-SER), combining image pyramid fitting, Zernike-moment edge extraction, and adaptive eccentricity-weighted fusion. Validated on simulated spots with varying SNRs and experimental sequences (visible off-axis aberration, long-wave infrared (LWIR) high-noise, MWIR micro-vibration), MSGF-SER achieved a noise-free RMSE of 0.03 pixel and 0.84 pixel at 5 dB SNR. On real MWIR vibration sequences, the Y-direction standard deviation (STD) dropped to 0.098 pixel, and the trajectory displacement variance was more than an order of magnitude lower than that of conventional methods. MTF deviations remained within 0.01, and the deviation of the measured mean EFL from the nominal focal length was better than 0.05 mm, and the STD was below 0.02 mm. These results demonstrate that MSGF-SER substantially improves centroid localization accuracy, repeatability, and smoothness under challenging conditions, providing reliable support for high-precision optical system parameter measurement. Full article

The field of infrared (IR) photodetection is undergoing rapid development through the emergence of solution-processable nanoparticle (NP)-based materials and fabrication strategies. This review critically examines recent advances in fabrication approaches for NP-based IR detectors, emphasizing the relationship between synthesis, surface engineering, deposition processes, and device architecture in determining detector performance. Representative material platforms are discussed, including colloidal quantum dots (CQDs) such as PbS and HgTe, which enable tunable operation from the near-infrared (NIR) and short-wave infrared (SWIR) to selected mid-wave (MWIR), long-wave (LWIR), and emerging very-long-wave infrared (VLWIR) regimes depending on material composition and operating conditions. Further platforms including plasmonic metal NPs, black phosphorus, and topological nanomaterials are evaluated for their unique mechanisms of optical enhancement and broadband response. Fabrication approaches including continuous-flow synthesis, ligand exchange, blade coating, inkjet printing, electrophoretic deposition, and other scalable solution-processing methods are analyzed with respect to their influence on film quality, charge transport, interface engineering, and integration compatibility. The review further compares major device architectures, including photoconductors, photodiodes, plasmonic absorbers, and phototransistors, using key performance metrics such as specific detectivity (D*), responsivity (R), response speed, and operating temperature, while emphasizing the importance of measurement conditions in cross-platform comparisons. Critical challenges including dark-current generation, 1/f noise, transport limitations associated with ligand chemistry, environmental instability of narrow-bandgap materials, manufacturability constraints, and toxicity considerations are also discussed. Emerging directions such as neuromorphic sensing, CMOS-compatible integration, and sustainable lead-free nanomaterials are highlighted. By linking nanoscale material design and fabrication processes to device-level performance, this review provides a framework for advancing NP-based IR technologies toward scalable and application-relevant sensing systems. Full article

Accurate cloud detection for geostationary infrared hyperspectral observations is important for the effective use of clear sky radiances in atmospheric retrieval and related applications. In this study, FY-4B/GIIRS observations were used to develop and evaluate three deep-learning cloud detection models, namely a conventional 1D-CNN (GCD-1D), a standard U-Net (GCD-U1), and a self-attention U-Net (GCD-U2). Cloud labels were generated by time-space matching between AGRI Level 2 cloud mask pixels and GIIRS field of views, and model performance was assessed using overall accuracy (OA), probability of detection (POD), and false alarm ratio (FAR) under different seasons, day/night conditions, and surface types. The results show that GCD-U2 achieved the best overall performance, with an OA of 85.88%, a POD of 77.07%, and a FAR of 24.40%, outperforming both GCD-1D and GCD-U1. The learned channel attention pattern was also physically consistent, with high weights assigned to LWIR window channels and selected MWIR bands. In the comparison with the GIIRS L2 operational cloud mask product, GCD-U2 showed higher consistency with the AGRI reference, with an average recognition–performance difference of about 10%. These results demonstrate the potential of attention-enhanced deep learning for operational cloud detection from geostationary infrared hyperspectral sounders. Full article

Chromatic aberration correction remains a major challenge in dual-band infrared continuous zoom optical systems. To address this issue, an achromatic design method based on the equivalent refractive index and equivalent dispersion rate is proposed. Starting from a four-component continuous zoom model, chromatic compensation is introduced into the initial structural parameter calculation, and the initial structural parameters are obtained through an iterative procedure. To validate the proposed method, a MWIR/LWIR dual-band continuous zoom optical system is designed. The final system covers the MWIR (3.7–4.8 μm) and LWIR (8–10 μm) bands with a focal length range of 10–120 mm, and the chromatic focal shift is controlled within the depth of focus. Clear imaging is achieved in both bands over the entire zoom range. These results demonstrate the effectiveness of the proposed achromatic strategy and provide a practical approach for the design of wide-band achromatic zoom optical systems. Full article

The Geostationary Interferometric Infrared Sounder (GIIRS) onboard the FengYun-4B weather satellite provides critical upwelling atmospheric infrared radiance. To address the limitations of the previous sounder (FY-4A/GIIRS) in terms of spatial resolution and spectral coverage, FY-4B/GIIRS has increased the spatial resolution to 12 km and added more spectral channels in the long-wave band to enhance the observation details and information content of weather systems. To evaluate its baseline performance, a comprehensive preflight test campaign—encompassing spectral and radiometric assessments—was conducted in a thermal vacuum (TVAC) chamber. Spectral characterization via laser measurements confirmed the instrument spectral response function (ISRF) is highly consistent with the theoretical cardinal sine function (sinc). Gas-cell tests demonstrated that, after correcting for off-axis effect, the spectral calibration errors are on average less than 5 ppm, validated against Line-By-Line Radiative Transfer Model (LBLRTM) simulations. The radiometric calibration employed temperature-variable blackbodies for noise performance and radiometric accuracy assessments. The radiometric sensitivity, characterized by Noise Equivalent differential Radiance (NEdR), is less than 0.5 and 0.1 mW/(m²·sr·cm⁻¹) in the long-wave infrared (LWIR) and mid-wave infrared (MWIR) bands, respectively. To address the LWIR detector nonlinearity, an iterative polynomial fitting algorithm based on spectral responsivity invariance was implemented. This correction reduces the radiometric deviation from >1.0 K to ~0.2 K, meeting the 0.7 K accuracy requirement across a 180–315 K dynamic range. Conversely, the MWIR band exhibits high linearity but is limited by noise when observing low-temperature scenarios and can only meet the 0.7 K requirement within the range of 250 to 315 K. Full article

This work investigates the feasibility of using thermographic techniques to identify the three possible states of a silicon-based coating on a carbon–silicon matrix (ISiComp). Experimental tests were therefore carried out on specimens prepared in three different conditions: uncoated, coated, and coated then oxidized. The study compares lock-in thermography and pulsed thermography using both a cooled mid-wave infrared (MWIR) camera and an uncooled long-wave infrared (LWIR) microbolometric camera. The main objective is to distinguish coated from uncoated conditions and oxidized from non-oxidized conditions, while recognizing that the coated and oxidized states cannot coexist simultaneously on the same specimen. The results show that thermographic techniques, when supported by appropriate post-processing, are promising for this purpose. In particular, the uncooled LWIR camera provided better results than the cooled MWIR camera, whereas the current approach did not allow a robust distinction between the pristine-coated and oxidized-coated states. At the same time, the study highlights limitations related to specimen size and to the additional treatments applied to reproduce the different surface states. Future work will address larger specimens and real components, together with the implementation of advanced AI-based classification algorithms to overcome the current limitations of the proposed approach. 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

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

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

Driven by the rising demand for digitalization and intelligent development of infrared payloads, next-generation systems must be developed within compressed timelines. High-precision digital modeling and simulation techniques offer essential data sources but often falter in complex space-based scenarios due to the limited availability of infrared characteristic data, hindering evaluation of the payload effectiveness. To address this, we propose a digital imaging simulation and verification (DISV) model for high-fidelity infrared image generation and closed-loop validation in the context of cloud–sea target detection. Based on on-orbit infrared imagery, we construct a cloud cluster database via morphological operations and generate physically consistent backgrounds through iterative optimization. The DISV model subsequently calculates scene infrared radiation, integrating radiance computations with an electron-count-based imaging model for radiance-to-grayscale conversion. Closed-loop verification via blackbody radiance inversion is performed to confirm the model’s accuracy. The mid-wave infrared (MWIR, 3–5 µm) system achieves mean square errors (RSMEs) < 0.004, peak signal-to-noise ratios (PSNRs) > 49 dB, and a structural similarity index measure (SSIM) > 0.997. The long-wave infrared (LWIR, 8–12 µm) system yields RMSEs < 0.255, PSNRs > 47 dB, and an SSIM > 0.994. Under 20–40% cloud coverage, the target radiance inversion errors remain below 4.81% and 7.30% for the MWIR and LWIR, respectively. The DISV model enables infrared image simulation across multi-domain scenarios, offering vital support for optimizing on-orbit payload performance. Full article

Colloidal quantum dots (QDs) have emerged as promising materials for the development of infrared photodetectors owing to their tunable band gaps, cost-effective manufacturing, and ease of processing. This paper provides a comprehensive overview of the fundamental properties of quantum dots and the operating principles of various infrared detectors. We review the latest advancements in short-wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (LWIR) detectors employing colloidal quantum dots. Despite their potential, these detectors face significant challenges compared to conventional infrared technologies. Current commercial applications are predominantly limited to the near-infrared and short-wave bands, with medium- and long-wave applications still under development. The focus has largely been on lead and mercury-based quantum dots, which pose environmental concerns, underscoring the need for high-performance, non-toxic materials. Looking forward, the development of large array and small pixel detectors and improving compatibility with readout circuits are critical for future progress. This paper discusses these hurdles and offers insight into potential strategies to overcome them, paving the way for next-generation infrared sensing technologies. Full article

Infrared (IR) sensors are widely used in various applications due to their ability to detect infrared radiation. Currently, infrared detector technology is in its third generation and faces enormous challenges. IR radiation propagation is categorized into distinct transmission windows with the most intriguing aspects of thermal imaging being mid-wave infrared (MWIR) and long-wave infrared (LWIR). Infrared detectors for thermal imaging have many uses in industrial applications, security, search and rescue, surveillance, medical, research, meteorology, climatology, and astronomy. Presently, high-performance infrared imaging technology mostly relies on epitaxially grown structures of the small-bandgap bulk alloy mercury–cadmium–telluride (MCT), indium antimonide (InSb), and GaAs-based quantum well infrared photodetectors (QWIPs), contingent upon the application and wavelength range. Nanostructures and nanomaterials exhibiting appropriate electrical and mechanical properties including two-dimensional materials, graphene, quantum dots (QDs), quantum dot in well (DWELL), and colloidal quantum dot (CQD) will significantly enhance the electronic characteristics of infrared photodetectors, transition metal dichalcogenides, and metal oxides, which are garnering heightened interest. The present manuscript gives an overview of IR sensors, their types, materials commonly used in them, and examples of related applications. Finally, a summary of the manuscript and an outlook on prospects are given. Full article

We present an innovative method for dual-band mid-wave infrared (MWIR) and long-wave infrared (LWIR) reflectors. By using double-sided metasurfaces, two high reflection bands can be generated with a single device. As individual guided-mode resonance (GMR) reflectors are combined with interlayer (or substrate) on the top and bottom sides, we achieved high reflection in the MWIR and LWIR bands simultaneously. Each GMR reflector was optimized as a germanium (Ge) grating structure on a potassium bromide (KBr) substrate. In our analysis, it was found that the transparency of the interlayer is critical to produce the dual-band reflection. The simulation results on the Ge/KBr/Ge double-sided metasurfaces demonstrated wideband reflection from ~3.3 to 4.8 μm and ~8.8 to 11 μm. Additionally, the device exhibited favorable angular tolerance. The work contributes to developing capability of metasurface technologies in various application fields. Full article