Applied optics最新文献

The self-calibration technique based on a spatially modulated snapshot Mueller matrix imaging polarimeter is proposed in this paper. Taking the snapshot Mueller matrix imaging polarimeter using modified Savart polariscopes as an example, it demonstrates that the self-calibration method can utilize frequency-domain information from independent channels to determine the spatial carrier frequency, thereby achieving frequency-domain filtering and demodulation instead of the traditional reference light calibration. This eliminates the inaccuracies introduced by the imprecise measurement of reference lights and environmental changes in the traditional calibration method, simplifies the experimental process, and removes biases caused by manual operations. The optical system design consists of two parts: the polarization state generator and the polarization state analyzer. Through the modulation of modified Savart polariscopes and half-wave plates, spatially separated interference fringes are generated. The modulation process employing Fourier transforms to the intensity of interference fringes yields 49 independent channels. Then, the demodulation process employing inverse Fourier transforms and subsequent mathematical operations on the information from each channel enables the reconstruction of 16 Mueller matrix elements. Theoretical analysis demonstrates that the system can accurately reconstruct the target's Mueller matrix using self-calibration algorithms, and its feasibility is validated through numerical simulation experiments. Experimental results show that the structural similarity index between the reconstructed images and the input target images exceeds 0.9, attaining favorable reconstruction outcomes. This technique provides a high-resolution, low-bias calibration solution for a spatially modulated snapshot Mueller matrix imaging polarimeter without using external reference lights. It holds significant application potential in biomedical science, materials research, remote sensing, and related fields.

Optical polarization imaging technology provides multi-dimensional light field information, encompassing spatial details and polarization data, which can be exploited for image semantic segmentation for target scene analysis. Most recent works focus on the development of neural networks with separate simple preprocessing steps to deal with the raw polarization images, which limit the accuracy of semantic segmentation. This paper proposes a novel, to the best of our knowledge, method, dubbed cascade deep polarization network (CDPN), to improve the performance of semantic segmentation by integrating preprocessing modules directly into the end-to-end deep learning work. The raw input data include the angle of linear polarization, degree of linear polarization, and a set of Stokes parameters. The multi-dimensional feature maps are extracted from the raw data through the image denoising, fusion, and enhancement modules, which are then concatenated with a backbone network to obtain the segmentation results. By collaboratively training the preprocessing modules and backbone network with self-supervised loss functions, we strive to find out the optimal segmentation solution. Experimental results show that the proposed method can effectively improve the segmentation accuracy, while maintaining fast computation speed.

We propose a method for fabricating integrated microresonators using conventional ultraviolet contact lithography. By a double-patterning scheme, the bus- and resonator-waveguide can be lithography-patterned individually with a single photoresist spinning and etching process. A sub-µm gap is achieved between the bus- and resonator-waveguides, which exceeds the resolution limitation between patterns of the conventional contact-lithography process. The quality (Q) factor of waveguide resonators can be up to ≈10⁴, while the maximum measured extinction ratio of the resonator is larger than 20 dB. This double-patterning method offers easy fabrication, low cost, and sub-µm pitches for silicon photonics.

Achieving uniform intensity distribution is essential for various laser applications such as material processing. This paper presents the design, simulation, and experimental validation of a segmented beam-shaping integrator mirror aimed at transforming an incident laser beam into a uniform line-shaped spot. The mirror surface is composed of multiple connected parabolic segments. A geometric optics computational method, implemented using Python code, was developed to determine the unique parameters and boundaries for each segment, based on input specifications including the working distance (f), the input aperture size (D), the target spot size (d), and the number of segments (s). For a design case with D=49.5mm, f=350mm, d=20mm, and s=7, the segment parameters were calculated. The calculated design was modeled in SolidWorks, and its performance was simulated using Zemax ray tracing, predicting a shaped spot closely matching the 20 mm target size in the segmented direction and an expected size (approx. 1.4 mm) in the orthogonal direction. Experimental validation was conducted using a 4 kW fiber laser equipped with a fiber core diameter of 400 µm and a numerical aperture of 0.15, along with a collimating lens with a 100 mm focal length. The measured spot size at the target plane was 20.39mm×1.41mm (1/e² width), showing excellent agreement with both the design specification and the simulation results. This work successfully demonstrates the effectiveness of the integrator mirror design method and fabrication process for creating high-performance beam-shaping integrator optics for high-power laser systems.

In laser radiometry, it is essential to evaluate the linearity of the detector and understand how interference effects influence power measurements, as laser light typically has high power and coherence. In this paper, we investigate the linearity and interference effects of widely used silicon photodiodes under the condition that they are coupled to an integrating sphere. For the linearity study, we employed a flux-addition method at 532 nm and found that one photodiode exhibited sufficient linearity, while the other showed supralinearity. This difference was attributed to whether the photodiode was irradiated with light outside its photoactive region. To further explore this, we examined the linearity by scanning the position of the laser irradiation on the photodiodes. In the interference study, we used a narrowband distributed Bragg reflector laser and measured the spectral responsivity by varying the laser wavelength. Due to the cover window, the spectral responsivity of photodiodes can rapidly vary as the wavelength changes under direct laser irradiation, with variations reaching up to tens of percent. However, when the spatial coherence of laser light is sufficiently suppressed by the integrating sphere, these rapid variations decrease to around 0.01% of the smoothly varying fitted values, which is negligible in typical laser power measurements.

We conducted a long-term aging test at high temperature on cubic glass rubidium vapor cells. The inner surface of the cubic glass cell was coated with Al₂O₃ using electron beam deposition, resulting in a thickness of 26.9 nm on the side walls and 63.8 nm on the bottom surface. The rubidium number density was monitored by measuring the absorption spectrum of the D₁ line. The measured spectrum was compared with a simulated profile based on the Beer-Lambert law. The rubidium number density in the Al₂O₃-coated rubidium vapor cell remained constant for nearly four times longer and then decreased 4.6 times more slowly than in the uncoated rubidium vapor cell.

Vanadium oxide (VOx) uncooled detectors are gaining increasing market share due to their small size, low cost, no cooling requirement, and reliable performance. However, as the pixel sizes of these detectors decrease, the problem of reduced absorptances becomes more prominent. To address this issue, this study proposes a "MIM+umbrella" metasurface VOx uncooled detector. Through simulation optimization, we achieved an average absorptance of over 97% in the long-wave infrared range and also demonstrated excellent absorption characteristics in the mid-infrared band. Furthermore, we validated and compared the contributions of this dual-layer metasurface to the absorptance of VOx uncooled detectors through fabrication and testing, demonstrating the feasibility and superiority of this structure.

Dissolution and diffusion in partially miscible liquid systems are prevalent physical phenomena. Parameters governing these processes, such as solubility (S) and diffusion coefficient (D), must be accurately measured for applications in biopharmaceuticals, chemical production, and food manufacturing. However, current common measurement methods are often time-consuming, require complex equipment, or lack accuracy, and they cannot measure both parameters simultaneously. In this study, we proposed a real-time optical image feature extraction method that utilizes the refractive-index spatiotemporal resolution capability of a compound liquid-core cylindrical lens to enable simultaneous assessment of S and D in partially miscible liquid systems. The D values of a glyceryl triacetate-water partially miscible system at five different temperature settings were measured using the equal-refractive-index thin-layer method based on the one-dimensional semi-infinite diffusion model, while S values were determined from the width of the image. The measured data at 298 K agreed with results obtained by other methods, confirming the reliability of the experiment and method. This method features a simple experimental setup and convenient operation, demonstrating broad application prospects.

We propose a blind deblurring method for retinal optical coherence tomography (OCT) images degraded by depth-dependent spatially variant blur. Our approach leverages an adaptive graph total variation (AGTV) prior, which dynamically adjusts regularization weights using local gradient statistics from the input image. AGTV autonomously enhances smoothing in severely blurred deep regions while preserving fine structures in shallow layers. Validated on microsphere images, en-face images, and B-scans, AGTV outperforms state-of-the-art methods in PSNR/SSIM metrics and significantly improves retinal layer segmentation accuracy-particularly for deep boundaries. This single-image framework requires no predefined PSF models or hardware modifications, offering a potential solution for clinical OCT enhancement.

The performance degradation of camouflaged object detection (COD) under complex backgrounds and dynamic illumination conditions has become a challenging issue in optical imaging and detection. To address the limitation of traditional visible-light imaging methods, which easily fail due to their inability to differentiate material and surface optical properties, a polarization-driven multimodal fusion network (PMFNet) is proposed in this paper. High-precision COD is achieved through iterative enhancement of polarization features. First, a feature rectification module is designed based on polarization differences induced by the surface scattering properties of objects. Second, a polarization-guided iterative refinement mechanism is developed, dynamically correcting texture degradation in RGB modality by employing high-resolution polarization features. Finally, a polarization adaptive fusion module is introduced to achieve context-aware complementary enhancement of RGB features through refined polarization information, thus deeply fusing complementary features of the two modalities. The proposed PMFNet demonstrates robust detection performance under adverse illumination and complex background conditions. Experimental results on public datasets demonstrate that the proposed PMFNet outperforms state-of-the-art COD methods.