Abstract:Although guided image filtering (GIF) is known for preserving edges and fast computation, it may produce inaccurate outputs in depth map restoration. In this paper, a novel confidence-weighted GIF called mutual-structure weighted GIF (MSWGIF) is proposed, which replaces the mean filtering strategy in GIF during handling overlapping windows. The confidence value is composed of a depth term and a mutual-structure term, where the depth term is utilized to protect the edges of the output, and the mutual-structure term helps to select accurate windows during the structure characteristics of the guidance image are transferred to the output. Experimental results show that MSWGIF reduces the root mean square error (RMSE) by an average of 12.37%, and the average growth rate of correlation (CORR) is 0.07% on average. Additionally, the average growth rate of structure similarity index measure (SSIM) is 0.34%.

Abstract:The integration of endoscopy has significantly propelled the diagnosis and treatment of gastrointestinal diseases, with colonoscopy establishing itself as the primary method for early diagnosis and preventive care in colorectal cancer (CRC). Although deep learning holds promise in mitigating missed polyp rates, modern endoscopy examinations pose additional challenges, such as image blurring and atomizing. This study explores lightweight yet powerful attention mechanisms, introducing the spatial-channel transformer (SCT), an innovative approach that leverages spatial channel relationships for attention weight calculation. The method utilizes rotation operations for inter-dimensional dependencies, followed by residual transformation, encoding inter-channel and spatial information with minimal computational overhead. Extensive experiments on the CVC-ClinicDB polyp detection dataset, addressing endoscopy pitfalls, underscore the superiority of our SCT over other state-of-the-art methods. The proposed model maintains high performance, even in challenging scenarios.

Abstract:As a laser passes through a scattering medium, the light interacts with the irregular reflections within the medium, resulting in light scattering and the formation of speckles. In this paper, an image sensor based on the combination of a coreless optical fiber and a digital camera is proposed for liquid refractive index sensing applications. The coreless fiber is used as a sensing unit, and the change in the speckle pattern is measured using the digital correlation method to detect the magnitude of the liquid’s refractive index. The experimental results indicate that the laser image sensing technique is capable of effectively distinguishing liquid samples with refractive indices ranging from 1.332 8 to 1.390 8, with a sensing sensitivity of −1.306 RIU-1. Moreover, the laser image sensing technique, with its advantages of high experimental reproducibility, simple system design, remote over-control, holds great research significance and potential application in laser communication and sensor integration.

Abstract:In this paper, we have calculated the structural, electronic, and optical properties of chalcogenide stannite Cu2CdSnX4 (X=S, Se, Te) materials. The calculations are based on the density functional theory (DFT) method and are performed using the Cambridge sequential total energy package (CASTEP) code included in the Biovia Material Studio 20 software. All optical properties have been studied in a domain that extends energetically from 10 meV to 40 eV. Our results show that Cu2CdSnX4 (X=S, Se, Te) stannite exhibits absorption in the visible region, the refractive index decreases with increasing energy, and the refractive index values are n=3.2, 3.73 and 3.75 for Cu2CdSnS4, Cu2CdSnSe4 and Cu2CdSnTe4, respectively. They show also high conductivity, which implies that this material is promising for solar cells. These results argue in favor of the use of these materials in various potential applications. The density of state, band structures, and structural properties of Cu2CdSnX4 (X=S, Se, and Te) stannite are also studied in this work.

Abstract:This paper proposes a lightweight reinforcement network (LRN) and auxiliary label distribution learning (ALDL) based robust facial expression recognition (FER) method. Our designed representation reinforcement (RR) network mainly comprises two modules, i.e., the RR module and the auxiliary label space construction (ALSC) module. The RR module highlights key feature messaging nodes in feature maps, and ALSC allows multiple labels with different intensities to be linked to one expression. Therefore, LRN has a more robust feature extraction capability when model parameters are greatly reduced, and ALDL is proposed to contribute to the training effect of LRN in the condition of ambiguous training data. We tested our method on FER-Plus and RAF-DB datasets, and the experiment demonstrates the feasibility of our method in practice during rehabilitation robots.

Abstract:Realizing the valley Hall effect by breaking the spatial inversion symmetry of photonic systems has become a cutting-edge field of micro-nano-optics, since the valley degree of freedom was introduced into photonic system. Various novel devices based on the domain walls of the valley photonic crystals have also been demonstrated. In this article, we investigate the variation of edge states by the modulation of refractive index within the domain walls, and the geometric difference between the dielectric columns of the sublattices. Straight photonic crystal waveguides with three types of domain walls (bearded, zigzag, armchair) are constructed. Simulation results show that the creation of a double-edge state in the band diagram results in two windows of stable transmission in tunable bands. Our findings might have significant implications in the field of novel optical devices.

Abstract:In order to better build the neutral beam injector with negative ion source (NNBI), the pre-research on key technologies has been carried out for the comprehensive research facility for fusion technology (CRFFT). Cesium seeding into negative-ion sources is a prerequisite to obtain the required negative hydrogen ion. The performance of ion source largely depends on the cesium conditions in the source. It is very necessary to quantitatively measure the amount of cesium in the source during the plasma on and off periods (vacuum stage). This article uses the absorption peak of cesium atoms near 852.1 nm to build a cesium atom concentration detection system based on tunable diode laser absorption spectroscopy (TDLAS) technology. The test experiment based on the cesium cell is carried out, and obtained the variation curve of cesium concentration at different temperatures. The experimental results indicate that the system detection range is within 5×106—2.5×107 pieces/cm3 and the system resolution better than 1×106 pieces/cm3.

Abstract:Atmospheric turbulence is an important parameter affecting laser atmospheric transmission. This paper reports on a self-developed atmospheric turbulence detection LiDAR system (scanning differential image motion LiDAR (DIM-LiDAR) system). By designing and simulating the optical system of atmospheric turbulence detection LiDAR, the basic optical imaging accuracy has been determined. By designing through electronics, the delay and gating time jitter of the system are kept within a small range, ensuring the accuracy of the sampling thickness of the optical column. The comparison observation results between the scanning DIM-LiDAR system and the ultrasonic anemometer show that both have the same trend of change, and the error is small. Long term observation results indicate that the scanning DIM-LiDAR developed based on optical and electronic design can effectively detect atmospheric turbulence profiles. This paper can provide theoretical and experimental basis for subsequent related research.

Abstract:To address the temperature cross-talk issue in detecting heavy metal ions in natural waters, a highly-integrated and fully fiber-optic metal ion sensing system capable of temperature-concentration decoupling measurement has been designed. This system integrates a fluidic detection structure assisted by side-polished fibers (SPFs) with a Sagnac interferometer. By selecting common refractive index ranges of contaminated water sources and common environmental temperature ranges, numerical simulations were conducted to analyze the sensing characteristics of the photonic bandgap boundary and interference spectrum wavelength in relation to these two parameters, and finally, a temperature and refractive index decoupling model was obtained. Results show that this system successfully demodulates the temperature parameter in solution refractive index sensing, exhibiting a concentration sensitivity of −355.96 nm∙mL/mol and a temperature interference of −2.03 nm/°C.

Abstract:We proposed a fiber optic high temperature sensor based on the Mach-Zehnder interference (MZI) structure, which is composed of two lengths of multi-mode fibers (MMFs), a length of few-mode fiber (FMF) and two sections of single-mode fibers (SMFs). Firstly, the two sections of MMFs were spliced with two sections of SMFs. Then, the MMFs were fused to two ends of FMF to form a symmetrically structured fiber-optic MZI structure. In this structure, the MMF served as the optical mode field coupling element, and the cladding and core of the FMF are the interference arm and the reference arm of the MZI structure, respectively. We investigated the sensor’s response characteristics of the temperature and strain. The experimental results indicate that the sensor is sensitive to temperature variation, and the temperature response sensitivity is up to 61.4 pm/℃ in the range of 40—250 ℃, while the sensor has weak strain sensitivity, its strain sensitivity is only −0.72 pm/με in the strain range of 0—1 400 με. Moreover, the sensor has good stability and repeatability. In brief, the proposed fiber optic high temperature sensor has good properties, such as high sensitivity, compact structure, good stability and repeatability, which can be used for monitoring the temperature of submerged oil electric pump units under oil wells.