Infrared Physics & Technology最新文献

{"title":"5-μm Tb3+ doped chalcogenide glass fiber laser with Bragg grating","authors":"V.V. Koltashev ,&nbsp;M.V. Sukhanov ,&nbsp;V.V. Likhov ,&nbsp;B.I. Denker ,&nbsp;B.I. Galagan ,&nbsp;S.E. Sverchkov ,&nbsp;E.N. Lashmanov ,&nbsp;A.P. Velmuzhov ,&nbsp;V.G. Plotnichenko ,&nbsp;A.G. Okhrimchuk","doi":"10.1016/j.infrared.2026.106455","DOIUrl":"10.1016/j.infrared.2026.106455","url":null,"abstract":"<div><div>Temperature tunable narrowband laser oscillations at 5 µm wavelength region were obtained in Tb-doped chalcogenide glass fiber due to feedback from the Bragg grating inscribed in it. The technique for direct laser writing of Bragg gratings in high refractive index chalcogenide fibers involves immersing the fiber into low-melting glass and helical motion of the lenticular beam waist of the femtosecond laser.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"155 ","pages":"Article 106455"},"PeriodicalIF":3.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146172871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Torsion-insensitive long-period fiber gratings via pre-twist assisted CO2 laser inscription","authors":"Zuyao Liu ,&nbsp;Jiaxin Luo ,&nbsp;Xinyi Zhao ,&nbsp;Lei Hong ,&nbsp;Chunfang Rao ,&nbsp;Yuanfeng Zhu ,&nbsp;Chengbo Mou ,&nbsp;Yunqi Liu","doi":"10.1016/j.infrared.2026.106458","DOIUrl":"10.1016/j.infrared.2026.106458","url":null,"abstract":"<div><div>We report the demonstration of a torsion-insensitive long-period fiber grating (LPFG) fabricated on pre-twisted single-mode fiber using the CO₂ laser point exposure method. By introducing a controlled pre-twist before inscription, the asymmetric refractive index modulation typically induced by point exposure evolves into a nearly circularly symmetric profile, leading to selective excitation of the LP₀₆ mode and suppression of asymmetric cladding modes such as LP₁₅ mode. Experimental result shows that increasing the pre-twist angle progressively reduces torsion sensitivity until nearly complete twist insensitivity is achieved, with a near-zero torsion sensitivity of −3.1 pm/(rad/m), while high temperature and refractive index sensitivities of 70.5 pm/°C and −250.1 nm/RIU, respectively, are preserved. The proposed strategy contrasts with previous pre-twist approaches aimed at enhancing torsion sensitivity, and instead provides a compact, fabrication-friendly route to realize twist-immune LPFGs. With its unique combination of ultra-low torsion response and strong environmental sensitivity, the LPFG is a promising candidate for deployment in demanding environments such as structural health monitoring.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"155 ","pages":"Article 106458"},"PeriodicalIF":3.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146172809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Infrared dim and small target detection based on spatiotemporal cascade low-rank sparse inversion","authors":"Xiangsuo Fan ,&nbsp;Tingting Li ,&nbsp;Yizhi Deng ,&nbsp;Biao Li ,&nbsp;Qingxiao Ma","doi":"10.1016/j.infrared.2026.106474","DOIUrl":"10.1016/j.infrared.2026.106474","url":null,"abstract":"<div><div>In the field of small target detection in the space domain, the traditional tensor model has insufficient constraints on noise and target features in the strong clutter environment, which leads to the residual problem of edge noise in the detection results. Firstly, a low-rank sparse inversion model with multi-dimensional spatiotemporal cascade jumps was constructed, and the accurate target extraction and preliminary filtering of background clutter in the background of strong clutter were realized by optimizing the low-rank sparse representation ability of the image matrix. Secondly, in order to solve the problem of aliasing of signals and noise caused by the uncertainty of the target trajectory in complex dynamic scenes, an energy enhancement model based on multi-directional motion estimation was designed. By establishing a hypothetical framework of nine-direction motion and combining it with the bilateral filtering weighting mechanism, the directional focusing enhancement of the target energy and the further suppression of the noise component are realized in the spatiotemporal dimension, and the target detection output with high SNR is finally completed. In the experimental part, the experimental part is compared with 11 small target detection methods in 8 typical scenes, and the results show that the proposed algorithm can effectively cope with the weak and small target detection tasks in complex scenes.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"155 ","pages":"Article 106474"},"PeriodicalIF":3.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilizing fabry-perot cavity filled with magnetic fluid and harmonic vernier effect to implement ultra-sensitive magnetic field vector detection","authors":"Yansheng Li,&nbsp;Hong Li,&nbsp;Xiaoshan Guo,&nbsp;Simei Sun,&nbsp;Huiling Huang,&nbsp;Tingshui Cao,&nbsp;Chao Jiang","doi":"10.1016/j.infrared.2026.106498","DOIUrl":"10.1016/j.infrared.2026.106498","url":null,"abstract":"<div><div>This article presents a magnetic field (MF) vector sensor based upon first-order harmonic vernier effect (HVE) and magnetic fluid. The sensor comprises two parallel Fabry–Perot interferometers (FPI) operating in the 1250 nm − 1650 nm infrared band: a sensing interferometer FPI₁ and a reference interferometer FPI₂. FPI₁ is formed by inserting single-mode fiber (SMF) at both ends of a magnetic fluid filled capillary tube and then encapsulating it. FPI₂ was constructed by inserting SMF at both ends of the capillary and encapsulating it to ensure high stability. The external MF will cause changes in the refractive index of the magnetic fluid in the capillary, making FPI₁ highly sensitive to the MF. Additionally, the change in MF direction can also affect the refractive index of the magnetic fluid, thereby achieving measurement of the MF direction. The HVE sensor S₁ was prepared by matching the F-P cavity length of FPI₁ and FPI₂. The MF experiment found that the sensitivity of MF strength measured using FPI₁ alone is 0.2321 nm/mT, and FPI₁ has the MF direction sensitivity of −0.0764 nm/°. S₁ has the MF strength sensitivity of 2.1556 nm/mT, and S₁ has the MF direction sensitivity of −0.5695 nm/°. S₁ can measure the MF vector, which increases the sensitivity of MF intensity by 9.3 times and the sensitivity of MF direction by 7.5 times compared to FPI₁ alone. In addition, S₁ has also high temperature sensitivity, with a temperature sensitivity of up to 11.30 nm/°C, and it also has the potential to measure temperature. The proposed sensor boasts characteristics of simple manufacture, low cost and highly-sensitive, which are widely used in MF measurement in major strategic fields of the country, such as geophysics, aerospace, deep-sea resource exploration, and nuclear industry.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"155 ","pages":"Article 106498"},"PeriodicalIF":3.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Compact trace gas sensing via single-cavity balanced-detection interferometric cavity-assisted photothermal spectroscopy","authors":"Johannes P. Waclawek,&nbsp;Harald Moser,&nbsp;Ufuk Yilmaz,&nbsp;Bernhard Lendl","doi":"10.1016/j.infrared.2026.106497","DOIUrl":"10.1016/j.infrared.2026.106497","url":null,"abstract":"<div><div>This work reports on the implementation of an alternative balanced-detection scheme to the ICAPS sensing method employing solely a single cavity. The new concept was realized by simultaneous detection of the interferometer’s reflectance and transmission. The use of only one cavity significantly reduces the system’s complexity in a balanced configuration by simplifying the detection architecture. Additionally, it increases the sensor’s sensitivity by noise cancellation and an improvement of the detectable signal up to a factor of 2. The set-up employed an optical cavity with a mirror spacing of 1  mm. A mid-infrared laser served as excitation source to induce refractive index changes in the sample, and a near-infrared laser served as probe source to monitor the photo-induced variations. The sensor’s metrological figures of merit were investigated by detection of CO. Moreover, the influence of varying water vapor concentration on the molecular relaxation of CO and thus the monitored photothermal signal employing a modulation frequency of ∼ 300  Hz was investigated. For the targeted absorption band centered at 2179.77  cm⁻¹ a 1σ minimum detection limit of 2 ppbv was achieved using an integration time of 1 s. This result corresponds to a normalized noise equivalent absorption of 7.4 × 10⁻⁹ cm⁻¹ W Hz^−1/2.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"155 ","pages":"Article 106497"},"PeriodicalIF":3.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building facade debonding damage detection method based on explainable artificial intelligence and UAV-thermography in cross scale field of view","authors":"Pengtao Wang ,&nbsp;Xiong Peng ,&nbsp;Yanqiu Nie ,&nbsp;Xingu Zhong ,&nbsp;Shouke Li ,&nbsp;Canlong Liu ,&nbsp;Cong Fang","doi":"10.1016/j.infrared.2026.106500","DOIUrl":"10.1016/j.infrared.2026.106500","url":null,"abstract":"<div><div>Debonding damage detection in building façades using UAV-thermography is essential for ensuring structural safety. However, three major challenges remain: detection is difficult in the cross scale field of view, model is insufficient under small sample data-set, model predictions lack explicability. To address these issues, this paper proposes a building facade debonding damage detection method based on explainable artificial intelligence. Firstly, a double attention enhanced C2f module (DA-C2f) is designed to effectively capture multi-scale information through simultaneous spatial and channel feature calibration; Then, an Omni-Dimensional Dynamic Convolution (ODConv) is employed to achieve multidimensional adaptive adjustment of convolution kernels; Simultaneously, the gradient-weighted class activation mapping (Grad-CAM) is introduced to generate heatmaps, constructing a visual explanation system. The results show that the proposed method achieves an accuracy of 85%, a recall of 84%, and a mean average precision (mAP) of 93.1% with 455 samples, significantly outperforming traditional state-of-the-art detection models.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"155 ","pages":"Article 106500"},"PeriodicalIF":3.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FDFusion: Efficient text-guided infrared-visible image fusion via fine-tuned lightweight VLM and Dual-branch feature modeling","authors":"Changhai Wang ,&nbsp;Zhe Huang ,&nbsp;Yuwei Xu ,&nbsp;Wanwei Huang ,&nbsp;Yuan Tian","doi":"10.1016/j.infrared.2026.106499","DOIUrl":"10.1016/j.infrared.2026.106499","url":null,"abstract":"<div><div>Infrared-visible image fusion plays a crucial role in enhancing scene perception in complex environments. Recent work has introduced large-scale Vision Language Models (VLMs) into the fusion pipeline to provide semantic priors. However, this reliance leads to substantial computational overhead. Furthermore, such approaches still exhibit notable shortcomings in preserving fine-grained textural details and effectively integrating high-level semantic information. To address these challenges, we propose <strong>FDFusion</strong>, an efficient text-guided infrared-visible image fusion framework based on a <strong>F</strong>ine-tuned lightweight VLM and <strong>D</strong>ual-branch feature modeling. Specifically, FDFusion employs a fine-tuned lightweight VLM to generate high-quality textual descriptions as prior information for guiding modal feature integration. It further incorporates a texture-semantic dual-branch modeling strategy to achieve more targeted semantic guidance. Additionally, we design a cross-layer attention module that establishes explicit alignment and selection mechanisms between features at different semantic depths. Experiments across multiple public datasets demonstrate that FDFusion outperforms state-of-the-art methods in information richness, texture preservation, gradient detail, and semantic consistency. Efficiency analysis further reveals that our fine-tuned lightweight model exhibits significant advantages in GPU memory consumption and inference latency compared to strategies relying on large-scale VLMs, while maintaining competitive fusion quality.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"155 ","pages":"Article 106499"},"PeriodicalIF":3.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MFDFuse: A multi-frequency decomposition-based network for infrared and visible image fusion","authors":"Hao Song ,&nbsp;Longkun He ,&nbsp;Shan Zhao,&nbsp;Lijin Gao,&nbsp;Chengjiang Zhou","doi":"10.1016/j.infrared.2026.106442","DOIUrl":"10.1016/j.infrared.2026.106442","url":null,"abstract":"<div><div>The infrared and visible image fusion is a technique that extracts and combines information from both images to enhance image quality and target recognition. The image fusion serves the high-level vision task. Therefore, existing fusion algorithms prioritize the prerequisites of these tasks, making it difficult to balance visual quality with task performance. Meanwhile, since the distribution of features is disordered and contains redundant information, the ability to directly capture features without constraints and targeting is limited. To address these issues, we propose an infrared and visible image fusion network based on multi-frequency feature decomposition, termed MFDFuse. Specifically, we build a channel-based collaborative feature extraction branch in the encoder to continuously capture and convey the correlations between channels, thus maintaining the coherence of channel modeling across the network to preserve the channel information of the source image. Secondly, we utilize element-wise multiplication-based single-level and multi-level mappings to integrate high-frequency information and semantic information, achieving a balance between detail preservation and semantic enhancement. Then, we propose a feature separation loss based on feature distance to separate low-high frequency features of different modalities to constrain the results of feature extraction. Finally, we fully consider the feature information lost during the feature extraction process to achieve effective compensation. The experiments performed on publicly accessible datasets, along with downstream tasks, have shown that MFDFuse surpasses state-of-the-art (SOTA) methods in both quantitative and qualitative analysis. The code is available at <span><span>https://github.com/SunsHine0816/MFDFuse.</span><svg><path></path></svg></span></div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"155 ","pages":"Article 106442"},"PeriodicalIF":3.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146172873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated symmetric equivalent layer design and stress compensation for high-performance infrared dual-band depolarizing beam splitters","authors":"Xingyu Cao ,&nbsp;Yuxiang Zhang ,&nbsp;Ben Wang ,&nbsp;Weibo Duan ,&nbsp;Xiuhua Fu ,&nbsp;Yue Hong ,&nbsp;Qian Zhang ,&nbsp;Yinghan Bi ,&nbsp;Shifu Xiong","doi":"10.1016/j.infrared.2026.106460","DOIUrl":"10.1016/j.infrared.2026.106460","url":null,"abstract":"<div><div>Depolarizing beam splitters are critical in Light Detection and Ranging (LiDAR) optical imaging systems to mitigate polarization effects, where spectral characteristics and surface precision directly govern laser transmission accuracy and quality. Achieving polarization uniformity across dual near-infrared bands while maintaining high surface accuracy is challenging due to material dispersion and film-stress coupling. Here, by integrating Costich’s depolarization theory with equivalent layer design, we engineered an optimized structure via a merit function in MATLAB and Macleod for 45° incidence across 895–915 nm and 1530–1565 nm. A pioneering dual-surface stress-balance strategy, establishing a precise mathematical relation between substrate sag and correction layer thickness, was devised to correct surface precision. This breakthrough directly resolves the polarization-accuracy conflict, overcoming the critical design bottleneck in dual-band depolarizing beam splitters. The beam splitter achieved average reflectance of 52.13% (p) &amp; 51.82% (s) in 895–915  nm, and 48.85% (p) &amp; 49.48% (s) in 1530–1565 nm, meeting 50 ± 3% spec with &lt; 2% deviation. Reflected wavefront RMS reached 0.0181λ (λ = 632.8  nm), fulfilling all system requirements. This work supplies a key component for advanced LiDAR imaging, breaks through material–stress limitations, and significantly promotes multi-band polarization-control optics development.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"155 ","pages":"Article 106460"},"PeriodicalIF":3.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146172870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AGMFNet: Attention-guided multi-scale feature fusion network for infrared small target detection","authors":"Shun He ,&nbsp;Jiaxue Liu ,&nbsp;Zhiwei Yang ,&nbsp;Ruirui Yuan","doi":"10.1016/j.infrared.2026.106483","DOIUrl":"10.1016/j.infrared.2026.106483","url":null,"abstract":"<div><div>In the process of identifying infrared small targets amidst intricate scenarios, they face problems such as few target pixels, complex backgrounds, and category imbalance. An attention-guided multi-scale feature fusion network (AGMFNet) is proposed. Firstly, to effectively integrate non-local context information and broaden the acceptance domain, a multi-scale receptive field expansion module(MRFE) structure is designed, and a dual-branch weighting mechanism is designed in MRFE, which improves the performance of the model and reduces the complexity of the model through the dynamic modification of the channel weights; Secondly, in the decoding process, to realize the effective integration of the low-level, middle-level and high-level features, ensure that the model can not only capture the details but also understand the semantics, to enhance its feature expression ability, we build a three-level asymmetric cross layer fusion (TACF) mechanism. Finally, a loss function is proposed to mitigate the imbalance between the background and the target of an infrared image, which enhances the network’s ability to recognize image details and structure. It makes it more focused on identifying target features. The experimental data show that AGMFNet achieves higher recognition accuracy and a lower rate of false alarms than other depth learning methods in complex scenes.</div></div>","PeriodicalId":13549,"journal":{"name":"Infrared Physics & Technology","volume":"155 ","pages":"Article 106483"},"PeriodicalIF":3.4,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}