Infrared Physics & Technology最新文献

Infrared thermal radiation emission in the 8.5 – 28 THz frequency region is obtained using surface metal–semiconductor grating structures on undoped (u-) GaAs, u-GaP, u-ZnO, u-GaN, and n-type SiC in a temperature range of 430 – 630 K. These emissions resonate with longitudinal optical (LO) phonon or LO-like lattice vibration energies determined by the zero points of the real parts of the dielectric functions in the surface structures. The emissions of materials with Reststrahlen bandwidths of a few tens of cm⁻¹ show the emissions resonating with their LO phonon modes, while materials with bandwidth of more than 170 cm⁻¹ show peak energies significantly lower than the LO phonon: LO-like phonon resonance. The emission intensity is found to be dominated by the balance of radiative and nonradiative LO or LO-like phonon annihilation rates. The radiative rate is dominated by the LO-phonon–radiation interaction Hamiltonian and the Bose-Einstein factor. High emission intensity is obtained for the structure on u-ZnO with intense LO-like phonon–radiation interaction. The dependence of the emission intensity on temperature and emission window width for various materials shows the effect of material-dependent metal/semiconductor interface conditions on the emission efficiency.

Exploring the characteristics of the instability and failure processes of gas-bearing coal and rock is crucial for monitoring and predicting mine gas accidents. Thus, a real gas environment was simulated based on a self-developed gas–solid coupling infrared observation system. The acoustic–thermal response characteristics and failure mode of the gas-bearing coal–rock composite structure were studied. The results showed the following: (1) From the plastic stage, the average infrared radiation temperature of the coal increased significantly. The variances of differential infrared temperature (VDIRT) of the combination and coal started to mutate approximately 30 s before the peak, and the b value of the combination began to fluctuate frequently, while the VDIRT of rock remained approximately 2.128 × 10⁻⁴ throughout the process. (2) When stress was about to peak, a clear temperature boundary formed between coal and rock. Acoustic emissions with high energy were mainly concentrated at the interface and inside the coal. (3) The early plastic stage was dominated by high-frequency, low-amplitude events. In the post-peak stage and late plastic stage, the proportion of events with 80–90 dB amplitude rose, and there was a significant increase in low-frequency, high-amplitude events. (4) As the loading proceeded, the density and area gradually increased and tended to move toward the shear crack region. The distribution range of the rise time/amplitude expanded from 0–12 ms/V at the beginning of the loading to the range of 0–60 ms/V in the post-peak stage.

The intention of infrared and visible image fusion is to combine the images captured by different modal sensors in the same scene to enhance its understanding. Deep learning has been proven its powerful application in image fusion due to its fine generalization, robustness, and representability of deep features. However, the performance of these deep learning-based methods heavily depends on the illumination condition. Especially in dark or exposed scenes, the fused results are over-smoothness and low-contrast, resulting in inaccuracy of object detection. To address these issues, this paper develops a multi-stage feature learning approach with channel-spatial attention mechanism, namely MSCS, for infrared and visible image fusion. The MSCS is composed of the following four key procedures: Firstly, the infrared and visible images are decomposed into illumination and reflectance components by a proposed network called as Retinex_Net. Then, the components are transported to an encoder for features coding. Next, we propose an adaptive fusion module with attention mechanisms to fuse the features. Finally, the fused image is generated by the decoder for decoding the fused features. Meanwhile, a novel fusion loss function and a multi-stage training strategy are proposed to train the above modules. The subjective and objective results of experiments on TNO, LLVIP and MSRS datasets illustrate that the proposed method is effective and performs better than the state-of-the-art fusion methods on achieving enjoyable results in dark or over-exposure scenes. And the results of further experiments on the fused images for object detection demonstrate that the fusion outputs produced by our MSCS are more beneficial for detection tasks.

A flexible single-polarization single-mode (SPSM) polymer/Ag-coated hollow waveguide with a racetrack-shaped cross-section was designed and prepared using a simple hot-pressing method and plasma treatment. The waveguide structural parameters were numerically optimized using the finite element method and the SPSM transmission can be achieved in a high birefringent (>0.8) hollow racetrack-shaped waveguide (HRW). The racetrack-like waveguides were facilely prepared by hot-pressing commercially available circular acrylonitrile butadiene styrene (ABS) and poly-ether-ether-ketone (PEEK) tubing, followed by plasma treatment and silver-plating. The HRW samples with a length of 40 cm were prepared, with a straight transmission loss of 1.74 and 1.68 dB/m at 0.1 THz, respectively, and the polarization degree is 99.9 %. When bent for 120° at a 10 cm radius or twisted by 90°, the waveguide samples have additional losses less than 0.22 and 0.14 dB/m, respectively, while the polarization degrees keep almost unchanged. After 200 h hydrothermal aging (85 RH%, 85 ℃) and 20 times high (85 ℃)/low (−40 ℃) temperature tests, the loss increase is less than 0.14 dB/m and the polarization degree remains unaffected. The HRW could be used in practice as a competitive substitute for traditional rectangular metal waveguides due to its high SPSM performance, lightweight, robustness, flexibility, and easy fabrication.

The thickness of the optically translucent coating was evaluated using the transmission thermography. The transmitted temperature of a two-layer structure was theoretically analysed based on the equation of 1D heat transfer in the depth direction, and accordingly, the method for the measurement of coating thickness in a two-layer structure was established based on a long-pulse transmission thermography. The coating thickness was determined based on the characteristic time at the maximum half-rise temperature. Then, the proposed method was experimentally validated and calibrated by coating specimen with a different coating thickness. The thickness measurement method was further applied to measure an uneven coating specimen fabricated by mechanical grinding. The measurements were compared with a 3D digital image correlation method and the averaged relative error was less than 4%. Finally, thermal excitation, sampling rate of thermography and translucence of organic coating were discussed for accurate measurement.

The main problem of infrared small target detection in complex background is how to effectively eliminate the edge residue. In this paper, we propose an efficient method named Superpixel Patch Image (SPI) model to handle this challenging task. The SPI model can fit the edges of the background well, thus effectively eliminating edge interference in the process of target detection, and achieving excellent performance. The SPI method consists of three steps: Firstly, an improved Simple Linear Iterative Clustering (ISLIC) algorithm is proposed to generate compact superpixels that perfectly match the background edge. Secondly, setting each superpixel patch as a column, a large patch-image matrix is constructed, and the target foreground image and background image is separated by imprecisely augmented Lagrange multiplication. Finally, based on the comprehensively analysis of the distribution characteristics of the target and the highlighted edge in the foreground image, an adaptive threshold is used to extract the target from the foreground superpixel patch. The experimental results of real infrared scenes show that the presented SPI model achieves the best SCRG, BSF and ROC curves compared with the existing 9 state-of-art algorithms, and can effectively extract small targets under different complex backgrounds.

The rapid development of infrared detection technology has generated an urgent demand for infrared camouflage, sparking widespread interest in low-emissivity materials. Novel material designs and advanced micro/nanofabrication technologies make it possible to realize materials with extremely low emissivity. However, a lower infrared emissivity does not always mean a better camouflage performance. There is a lack of sufficient discussion on how to determine an appropriate emissivity for a specific working condition to achieve effective infrared camouflage. Here, through outdoor experiments, we demonstrated that for a specific scenario, an appropriate emissivity always exists that can make the infrared characteristics of the target effectively blend into its background, and deviations from the emissivity result in deteriorated camouflage performance. Further, we established a heat transfer model to conduct quantitative analysis on the influence of emissivity on infrared camouflage performance in terms of surface temperature and radiative temperature in various conditions. In addition, we proposed a general method for determining the optimal emissivity of infrared camouflage, defined as the emissivity value at which the radiative temperatures of the target and the background are equal. To facilitate practical application of this method, we developed a user-friendly MATLAB app named “Optimal Emissivity Calculator” to calculate the optimal emissivity. It was found that for a vehicle’s engine compartment surface at approximately 340.0 K, the optimal emissivity is 0.4 with a background temperature of 300.0 K. This work highlights the significance of selecting appropriate emissivity for infrared camouflage and provides a reference for designing the emissivity of infrared camouflage materials.

With the widespread use of multi-spectrum detection technology, the stealth of a single frequency band cannot meet the practical application requirements. Recently, the investigation of wearable and insulated multi-spectrum compatible stealth technology has become urgent. The flexible and thermally isolated wideband microwave meta-absorber with infrared and visible camouflage has been proposed, fabricated, and measured. An infrared shielding layer (IRSL) and a radar absorbing layer (RAL) are the two main components of the absorber. IRSL is realized by specifically arranging the pre-designed patch structure with three different filling ratios, which can confuse the detection of thermal infrared in 3–14 μm. RAL is achieved by etching the structure of the lossy material to form electrical loss in plane and magnetic loss between layers, so as to realize the broadband absorption of microwave higher than 90 % from 6.2-22.2 GHz. In addition, the absorber employs flexible and thermally isolated materials, providing excellent high-temperature stability normally at temperatures up to 130 °C. These unique properties confirm the feasibility of the proposed strategy. To effectively adapt to different thermal camouflage environments, it is essential to create IR digital camouflage patterns. Moreover, the additional flexibility and thermal insulation characteristics make it powerful in compatible camouflage-stealth facilities when used in complex environments and a wide range of high temperatures.

Cracks can develop obliquely to the metal surface. The multi-speed laser lock-in thermography method is suited for the contactless estimation of open crack angles and depths in metal with oblique linear cracks. A continuous laser source regularly scans the studied sample leading to a periodical heating. The heat diffusion disturbances induced by a crack located in the thermal diffusion area are measured synchronously with the repeated continuous laser scan passes. The thermal signature of the crack is extracted from the amplitude of surface temperature images for various scanning speeds of the thermal source. The asymmetry of the thermal signatures obtained on each side of the crack is analysed as a function of a length relying on the thermal diffusion length. The local crack depth and crack angle are evaluated simultaneously. The method, explained with 3D simulations, is experimentally implemented and tested with calibrated oblique linear cracks. The results demonstrate the potentiality of multi-speed laser lock-in thermography method as a contactless measurement tool for the evaluation of oblique crack shapes up to 3.5 mm depth.

The fusion of multi-modal images to create an image that preserves the unique features of each modality as well as the features shared across modalities is a challenging task, particularly in the context of infrared (IR)-visible image fusion. In addition, the presence of polarization and IR radiation information in images obtained from IR polarization sensors further complicates the multi-modal image-fusion process. This study proposes a fusion network designed to overcome the challenges associated with the integration of low-resolution IR, IR polarization, and high-resolution visible (VIS) images. By introducing cross attention modules and a multi-stage fusion approach, the network can effectively extract and fuse features from different modalities, fully expressing the diversity of the images. This network learns end-to-end mapping from sourced to fused images using a loss function, eliminating the need for ground-truth images for fusion. Experimental results using public datasets and remote-sensing field-test data demonstrate that the proposed methodology achieves commendable results in qualitative and quantitative evaluations, with gradient based fusion performance $Q^{\mathrm{AB}/F}$, mutual information (MI), and $Q_{\mathrm{CB}}$ values higher than the second-best values by 0.20, 0.94, and 0.04, respectively. This study provides a comprehensive representation of target scene information that results in enhanced image quality and improved object identification capabilities. In addition, outdoor and VIS image datasets are produced, providing a data foundation and reference for future research in related fields.