Chen Xu

Laser scanning systems are adopted for diverse applications in imaging, printing, and material processing, and there is a growing trend toward volume miniaturization without compromising optical performance. In this work, a highly compact optical configuration is proposed by combining catadioptric architecture with freeform optics. A multi-stage design method, from starting point acquisition to fine-tuning, is proposed, with particular attention to concurrently controlling physical layout and optical performance. Two systems were designed, demonstrating an average RMS wavefront error below 0.006λ and a linearity error under 0.3% over a 216 mm scanning width. The spot size deviation is below ±9%, and the position deviation is kept within half the diffraction-limited spot diameter over a ±2 mm depth of field. Compared to a conventional freeform lens design, the proposed systems reduce the total length by over 37.7%. The significant reduction in size achieved paves the way for next-generation portable and embedded laser scanning devices.

Rapid and quantitative measurement of the bidirectional scattering distribution function (BSDF) is essential for characterizing both reflective and transmissive scattering properties of optical materials. Existing rapid image-based instruments have achieved efficient bidirectional reflectance distribution function (BRDF) measurement, but integrating BRDF/BTDF capability, compact optical architecture, and multispectral quantitative calibration remains challenging. This paper presents a compact multispectral image-based BSDF measurement system that extends our previous BRDF instrument to integrated reflection and transmission characterization. A dedicated bidirectional transmittance distribution function (BTDF) illumination module is incorporated to enable dual-side measurement within a fully enclosed structure. To accommodate this configuration while preserving wide-field imaging performance, the catadioptric collection system is redesigned using a polynomial-corrected ellipsoidal primary reflector. The added surface degrees of freedom compensate for off-axis asymmetric aberrations, reducing the primary reflector diameter from 200 mm to 100 mm while maintaining a maximum collection field of view of 75°. The prototype acquires eight-band single-exposure data within 30 s for each incidence angle and achieves average angular resolutions of approximately 1.2° for BRDF and 0.8° for BTDF. A geometric and spectrophotometric calibration framework is established using reference BSDF data acquired from a goniospectrometer, with spectral-band integration matched to the multispectral camera response. Validation using standard color tiles and translucent PMMA samples shows root-mean-square errors below 0.008 under the tested reflection and transmission conditions. The baseline combined relative standard uncertainty, evaluated using diffuse reference samples, is estimated to be 3.5%. Multispectral BSDF mapping of a Morpho butterfly wing further demonstrates rapid visualization of anisotropic spatial-spectral scattering.

Traditional full-field optical coherence tomography (FF-OCT) systems face limitations in imaging efficiency and data redundancy, particularly when applied to complex biological samples. To address these issues, we developed an automated FF-OCT system that uses a variable resolution z-scanning strategy to dynamically adjust the voxel resolution of acquired images according to sample structures. The system was validated using 3D HepaRG cell cultures embedded in micro-hydrogels. To optimize imaging efficiency and minimize data redundancy, an in-air voxel resolution of 0.7×0.7×5µm³ was applied to the region of interest (ROI) for detailed sample analysis, while a lower resolution of 1.4×1.4×10µm³ was used in non-ROI areas. Compared to traditional equidistant acquisition methods, the variable resolution strategy reduced imaging time by over 20% and data storage requirements by more than 35%, with deviations in morphological parameters, including volume and surface area, kept below 1%. Robustness tests across multiple cell culture batches confirmed the system’s reliability in accurately capturing complex biological structures. This study demonstrates a significant advancement in FF-OCT technology, providing a practical, high-efficiency, and high-precision solution for non-invasive imaging of complex biological samples.

In this study, we propose an effective design method for a compact freeform f-θ lens system for 3D printing laser scanning units. A two-phase design strategy based on surface-type upgrade is put forward for the design of the f-θ lens, where different models and design targets are adopted at different stages in optimization. An automatic linearity error correction procedure is proposed to replace the tedious manual adjusting process. A design result comparable with the A4 scanning width was obtained following the proposed design strategy. The relative difference in diffraction spot size is below 3.05% in ±100mm scanning width, and the linearity error stays below 0.3%, indicating a good optical performance. The tolerance performance and thermal analysis show that the design result meets the requirement in real usage conditions.

This article proposes a new method for designing an optical transparent frequency-selective surface absorber using indium tin oxide (ITO) conductive film with different sheet resistances. This novel optical transparent frequency-selective absorber exhibits excellent optical transparency, ensuring a visible light transmittance exceeding 76%. Simultaneously, it exhibits broadband absorption characteristics covering the entire X-Ku band, with an absorption rate exceeding 90%. Due to the simplicity of the design, the overall structure is easily processable, and the desired product can be rapidly fabricated using laser etching equipment without adding any lumped elements in the design. Simulation and experimental results indicate that the S11–10 dB frequency range of the frequency-selective absorber is 7.7–18.4 GHz, with a transmission frequency range below −3 dB between 26.7–29.4 GHz. The findings suggest that this structure holds potential applications in microwave stealth design requiring optical transparency and high-throughput satellite communication scenarios.

By utilizing a catadioptric system and a calibration Lambertian sample, a compact measurement method of bidirectional reflectance distribution function (BRDF) has been proposed for rapid and accurate measurement. With the help of an ellipsoidal dome mirror, a hyperboloid mirror, and a high-resolution camera, spatial reflectance distributions from reflected directions with a large field of view (FOV) can be obtained. The built-in Lambertian standard allows for real-time calibration to account for fluctuations in the illumination spectrum, effectively reducing the measurement drift and achieving a high accuracy. Moreover, a multispectral camera captures images at 8 spectral bands for accurate spectral color reconstruction from different directions. To verify the method, a prototype capable of fast, high-resolution measurements with a large FOV has been developed for characterizing the scattering properties of objects. It achieves a measured angular range up to 160°. Multispectral BRDF data for each sample can be obtained within 5 minutes with an angular resolution of less than 0.6°. Eight ceramic samples with different colors were selected for the verification of measurement accuracy, and their mean relative bias of BRDF measurement was found to be as low as 2.5%.

We consider the problem of hyperspectral image (HSI) reconstruction, which aims to recover 3D hyperspectral data from 2D compressive HSI measurements acquired by a coded aperture snapshot spectral imaging (CASSI) system. Existing deep learning methods have achieved acceptable results in HSI reconstruction. However, these methods did not consider the imaging system degradation pattern. In this paper, based on observing the initialized HSIs obtained by shifting and splitting the measurements, we propose a dynamic Fourier network based on degradation learning, called the degradation-aware dynamic Fourier-based network (DADF-Net). We estimate the degradation feature maps from the degraded hyperspectral images to realize the linear transformation and dynamic processing of the features. In particular, we use the Fourier transform to extract the HSI non-local features. Extensive experimental results show that the proposed model outperforms state-of-the-art algorithms on simulation and real-world HSI datasets. The source code is available at: https://github.com/CISMOLab/DADF-Net

Ultraviolet (UV) irradiation causes 90% of photodamage to skin and long-term exposure to UV irradiation is the largest threat to skin health. To study the mechanism of UV-induced photodamage and the repair of sunburnt skin, the key problem to solve is how to non-destructively and continuously evaluate UV-induced photodamage to skin. In this study, a method to quantitatively analyze the structural and tissue optical parameters of artificial skin (AS) using optical coherence tomography (OCT) was proposed as a way to non-destructively and continuously evaluate the effect of photodamage. AS surface roughness was achieved based on the characteristic peaks of the intensity signal of the OCT images, and this was the basis for quantifying AS cuticle thickness using Dijkstra’s algorithm. Local texture features within the AS were obtained through the gray-level co-occurrence matrix method. A modified depth-resolved algorithm was used to quantify the 3D scattering coefficient distribution within AS based on a single-scattering model. A multiparameter assessment of AS photodamage was carried out, and the results were compared with the MTT experiment results and H&E staining. The results of the UV photodamage experiments showed that the cuticle of the photodamaged model was thicker (56.5%) and had greater surface roughness (14.4%) compared with the normal cultured AS. The angular second moment was greater and the correlation was smaller, which was in agreement with the results of the H&E staining microscopy. The angular second moment and correlation showed a good linear relationship with the UV irradiation dose, illustrating the potential of OCT in measuring internal structural damage. The tissue scattering coefficient of AS correlated well with the MTT results, which can be used to quantify the damage to the bioactivity. The experimental results also demonstrate the anti-photodamage efficacy of the vitamin C factor. Quantitative analysis of structural and tissue optical parameters of AS by OCT enables the non-destructive and continuous detection of AS photodamage in multiple dimensions.

Hyperspectral images (HSIs) contain rich spatial and spectral information. A double dispersers coded aperture snapshot spectral imaging (DD-CASSI) system takes advantage of compressive sensing (CS) theory to map 3D HSI data into a single 2D measurement. One of key components of DD-CASSI is to reconstruct high quality hyperspectral image from measurement. Traditional model-based methods use mathematical optimization to reconstruct hyperspectral images according to prior knowledge. Current deep learning based methods achieve pleasant results. But fully learned deep learning methods lack interpretability, and model-based deep learning methods cannot achieve pleasant performance. In this paper, we propose a novel HSI reconstruction framework named Refinement Boosted and Attention Guided Tensor FISTA(Fast Iterative Shrinkage-Thresholding Algorithm)-Net (ReAttFISTA-Net), which combines model-based deep learning and fully learned deep learning reconstruction strategies. In this framework, we introduces Attention Guided Fusion Mechanism which enhances spatial-spectral information, refinement sub-network and auxiliary loss terms to improve the reconstruction performance. Extensive experimental results show that the proposed reconstruction algorithm outperforms the state-of-the-art algorithms on both simulation and real-world datasets.