Optics and Laser Technology最新文献_第9页

FDIFusion: A fusion-decoupling framework with implicit neural representation for infrared and visible image fusion FDIFusion：一种具有隐式神经表示的红外和可见光图像融合解耦框架

IF 5 2区物理与天体物理

Optics and Laser Technology Pub Date : 2025-09-18 DOI: 10.1016/j.optlastec.2025.113895

Wenmiao Shi , Rencan Nie , Jinde Cao , Jiang Zuo , Xiaoyu Li

{"title":"FDIFusion: A fusion-decoupling framework with implicit neural representation for infrared and visible image fusion","authors":"Wenmiao Shi , Rencan Nie , Jinde Cao , Jiang Zuo , Xiaoyu Li","doi":"10.1016/j.optlastec.2025.113895","DOIUrl":"10.1016/j.optlastec.2025.113895","url":null,"abstract":"<div><div>Infrared and Visible Image Fusion (IVIF) aims to combine the complementary advantages of infrared and visible images to produce high-quality fused images with enhanced clarity and information content. Traditional methods often fail to independently process infrared and visible images, thereby missing the opportunity to fully exploit their complementary information. To address this issue, we propose an innovative framework that employs implicit neural representation (INR) for progressive fusion and decoupling. Our framework incorporates a triple-branch, multi-resolution network designed to minimize information loss during fusion and effectively extract features from infrared and visible modalities. By integrating a decoupling model, our method reduces redundancy and enhances the independence of fused features. Furthermore, INR enables continuous feature representation across network layers, which enhances structural continuity and semantic consistency in the fused image. This, in turn, facilitates the preservation of fine details and improves visual perception. Experimental results demonstrate that our proposed FDIFusion method strikes an optimal balance between salient structures and fine textures, achieving significant quantitative and qualitative improvements over existing methods. In addition, FDIFusion exhibits excellent generalization ability and has great potential for real-world applications in complex scenarios.</div></div>","PeriodicalId":19511,"journal":{"name":"Optics and Laser Technology","volume":"192 ","pages":"Article 113895"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

Coupling characteristics of nonuniform tapered fiber waveguide for free-space optical communication 自由空间光通信中非均匀锥形光纤波导的耦合特性

IF 5 2区物理与天体物理

Optics and Laser Technology Pub Date : 2025-09-18 DOI: 10.1016/j.optlastec.2025.113910

Baoqun Li , Tianshu Wang , Gang Deng , Shaoqian Tian , Deqi Li , Tianjiao Wu , Sunde Wang , Shutong Liu , Silun Du

{"title":"Coupling characteristics of nonuniform tapered fiber waveguide for free-space optical communication","authors":"Baoqun Li , Tianshu Wang , Gang Deng , Shaoqian Tian , Deqi Li , Tianjiao Wu , Sunde Wang , Shutong Liu , Silun Du","doi":"10.1016/j.optlastec.2025.113910","DOIUrl":"10.1016/j.optlastec.2025.113910","url":null,"abstract":"<div><div>A high-stability reception scheme for single-mode optical signal based on non-uniform tapered fiber waveguide (NTFW) is proposed and experimentally verified to suppress severe power fluctuation in single-mode optical signal caused by atmospheric turbulence within free-space optical communication (FSO). With the high tolerance characteristic of NTFW in radial misalignment, this scheme significantly reduces the jitter amplitude of the received single-mode laser signal and effectively improves the detection sensitivity of free-space optical communication under turbulent condition. Experimental results show that under atmospheric turbulence condition with coherence length r<sub>0</sub> = 0.657 cm, the detection sensitivity exhibits a positive correlation with the core diameter of the NTFW when the average received power ranges from −15 dBm to −35 dBm. Compared to standard single-mode fiber (SMF), when the bit error rate (BER) reaches the forward error correction limit, the detection sensitivity is improved by 4.367 dB, 12.197 dB, and 15.245 dB using NTFWs with core diameters of 15 μm, 20 μm, and 25 μm, respectively. The research results provide a new approach to enhancing the robustness of single-mode FSO while reducing the accuracy requirements for terminal servo system, demonstrating strong potential for engineering applications.</div></div>","PeriodicalId":19511,"journal":{"name":"Optics and Laser Technology","volume":"192 ","pages":"Article 113910"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

Information-quantitative evaluation of linear computational imaging and application in ghost imaging 线性计算成像的信息定量评价及其在鬼影成像中的应用

IF 5 2区物理与天体物理

Optics and Laser Technology Pub Date : 2025-09-18 DOI: 10.1016/j.optlastec.2025.113893

Long-Kun Du , Chenyu Hu , Zhen-Wu Nie , Chen Chang , Shuai Sun , Shuang Liu , Chenjin Deng , Zunwang Bo , Wei-Tao Liu , Shensheng Han

{"title":"Information-quantitative evaluation of linear computational imaging and application in ghost imaging","authors":"Long-Kun Du , Chenyu Hu , Zhen-Wu Nie , Chen Chang , Shuai Sun , Shuang Liu , Chenjin Deng , Zunwang Bo , Wei-Tao Liu , Shensheng Han","doi":"10.1016/j.optlastec.2025.113893","DOIUrl":"10.1016/j.optlastec.2025.113893","url":null,"abstract":"<div><div>Current evaluation of imaging systems mainly relies on comparing the imaging results to the ground truth. However, the ground truth is usually unavailable in practical scenarios. In this paper, we propose a framework for assessing the capabilities of linear computational imaging processes, where the mapping between object and measurements can be modeled as linear. This framework utilizes Bayesian approach to estimate the amount of acquired information from each sampling, independent of the imaging results and ground truth. We demonstrated our framework based on ghost imaging, a typical linear computational imaging system. This-method facilitates image quality to be improved to the Cramér–Rao bound. Furthermore, an adaptive design of the imaging procedure is also developed and integrated into this dynamic evaluation framework to improve the ability to capture information. The proposed framework exhibits intrinsic generalizability to linear computational imaging systems, and its theoretical structure allows for potential extensions to other computational imaging paradigms.</div></div>","PeriodicalId":19511,"journal":{"name":"Optics and Laser Technology","volume":"192 ","pages":"Article 113893"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

One step measurement of spatiotemporal distributions of refractive-index structure parameter using deep learning 利用深度学习一步测量折射率结构参数的时空分布

IF 5 2区物理与天体物理

Optics and Laser Technology Pub Date : 2025-09-17 DOI: 10.1016/j.optlastec.2025.113921

Weihao Cheng , Yunyun Chen , Chuangan Yun , Zhiqin Huang , Fenping Cui , Bing Tu

{"title":"One step measurement of spatiotemporal distributions of refractive-index structure parameter using deep learning","authors":"Weihao Cheng , Yunyun Chen , Chuangan Yun , Zhiqin Huang , Fenping Cui , Bing Tu","doi":"10.1016/j.optlastec.2025.113921","DOIUrl":"10.1016/j.optlastec.2025.113921","url":null,"abstract":"<div><div>Accurate measurement of the spatiotemporal distributions of the refractive-index structure parameter is crucial for characterizing atmospheric turbulence intensity and visualizing turbulent flow fields. However, traditional method remains limited by their computational complexity and inefficiency. In this paper, a One-step method for Refractive-index structure parameter Spatiotemporal distributions Measurement based on Deep Learning (DLORSM) is proposed. This method enables the direct one-step prediction of the spatial distributions of the refractive-index structure parameter in two directions using deep learning model and subsequently derives its temporal distributions. Numerical simulations are conducted to compare the DLORSM method with traditional method. The results show that DLORSM method achieves significantly lower errors of 0.17% and 0.16% in estimating spatiotemporal distributions, demonstrating its high accuracy and robustness. Experimental validation under real atmospheric conditions further confirms that DLORSM effectively captures the random fluctuations and structural characteristics of real atmospheric flow fields. This study lays a foundational framework and provides valuable insight into the intelligent measurement of spatiotemporal distributions of atmospheric refractive-index structure parameters using deep learning.</div></div>","PeriodicalId":19511,"journal":{"name":"Optics and Laser Technology","volume":"192 ","pages":"Article 113921"},"PeriodicalIF":5.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

Modeling and compensation of specular reflection errors in laser displacement sensors for complex curved surface measurements 复杂曲面激光位移传感器镜面反射误差建模与补偿

IF 5 2区物理与天体物理

Optics and Laser Technology Pub Date : 2025-09-17 DOI: 10.1016/j.optlastec.2025.113909

Jiating An, Min Xu, Daixin Huang, Lingbao Kong

{"title":"Modeling and compensation of specular reflection errors in laser displacement sensors for complex curved surface measurements","authors":"Jiating An, Min Xu, Daixin Huang, Lingbao Kong","doi":"10.1016/j.optlastec.2025.113909","DOIUrl":"10.1016/j.optlastec.2025.113909","url":null,"abstract":"<div><div>Laser displacement sensors (LDS) provide non-contact precision measurement capabilities but suffer from accuracy degradation when measuring complex curved surfaces due to specular reflection interference. Existing approaches either require hardware modifications or lack systematic theoretical foundations for understanding error mechanisms and implementing effective compensation strategies. This study establishes a comprehensive theoretical framework for specular reflection-induced measurement errors in laser triangulation systems. Our theoretical analysis reveals that surface inclination angle is the primary error source, with specific angular ranges producing critical measurement deviations. The investigation demonstrates that optical system parameters error region characteristics while surface texture properties control error magnitude. Based on these theoretical foundations, we implement a hardware-free compensation strategy utilizing wavelet transform algorithms for automated error detection and adaptive correction. Experimental validation across inclined test planes and spherical surfaces with varying textures confirm theoretical analysis. The compensation method achieves peak-to-valley error reduction to 4.06 μm and root means square error reduction to 0.61 μm, representing approximately 46 % accuracy improvement over conventional measurement approaches. This research advances theoretical understanding of specular reflection-induced errors in LDS and provides a practical solution for high-precision measurement of complex curved surfaces.</div></div>","PeriodicalId":19511,"journal":{"name":"Optics and Laser Technology","volume":"192 ","pages":"Article 113909"},"PeriodicalIF":5.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

Lightweight Arbitrary-Scale Super-Resolution via Texture-Aware deformation 通过纹理感知变形的轻量级任意尺度超分辨率

IF 5 2区物理与天体物理

Optics and Laser Technology Pub Date : 2025-09-17 DOI: 10.1016/j.optlastec.2025.113922

Haoran Jia , Pengjie Zhao , Tongtai Cao , Xin Wang , Yue Liu

{"title":"Lightweight Arbitrary-Scale Super-Resolution via Texture-Aware deformation","authors":"Haoran Jia , Pengjie Zhao , Tongtai Cao , Xin Wang , Yue Liu","doi":"10.1016/j.optlastec.2025.113922","DOIUrl":"10.1016/j.optlastec.2025.113922","url":null,"abstract":"<div><div>Single-image super-resolution (SISR) has achieved remarkable progress through deep learning, yet mainstream SISR methods typically rely on fixed-scale up-sampling designs, struggling to balance reconstruction quality with computational efficiency across arbitrary scales, thereby limiting their practical flexibility. Although prior studies have attempted to incorporate positional and scale information for arbitrary-scale image super-resolution (ASISR), challenges remain in modeling cross-scale texture degradation characteristics. To address this, we propose two lightweight, structured plug-in modules that seamlessly integrate into existing SISR architectures, significantly enhancing their arbitrary-scale image modeling and reconstruction capabilities. Specifically, we design a Texture-Aware Deformation Up-sampling Module (TADUM), which captures scale-dependent texture deformation patterns by fusing position and scale-aware information to generate dynamic adaptive filters, enabling precise reconstruction at arbitrary scales. Furthermore, we introduce a Scale-Aware Image Refinement Module (SAIRM) that employs a multi-scale feature guidance mechanism and dynamic detail enhancement strategy to effectively maintain cross-scale visual consistency. Experimental results demonstrate that our approach significantly enhances reconstruction performance at non-integer scales while maintaining superior performance at standard integer scales, fully validating its efficiency, accuracy, and generalization in handling scale-sensitive tasks.</div></div>","PeriodicalId":19511,"journal":{"name":"Optics and Laser Technology","volume":"192 ","pages":"Article 113922"},"PeriodicalIF":5.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

Boosting robust multimodal point cloud registration via tightly-coupled framework of visual and geometric features 通过视觉和几何特征的紧密耦合框架增强多模态点云配准的鲁棒性

IF 5 2区物理与天体物理

Optics and Laser Technology Pub Date : 2025-09-17 DOI: 10.1016/j.optlastec.2025.113917

Zhangji Lu , Chengbo Zhang , Zewei Cai , Junyi Zhang , Xiang Peng , Qijian Tang , Xiaoli Liu

{"title":"Boosting robust multimodal point cloud registration via tightly-coupled framework of visual and geometric features","authors":"Zhangji Lu , Chengbo Zhang , Zewei Cai , Junyi Zhang , Xiang Peng , Qijian Tang , Xiaoli Liu","doi":"10.1016/j.optlastec.2025.113917","DOIUrl":"10.1016/j.optlastec.2025.113917","url":null,"abstract":"<div><div>In large-scale scene reconstruction using multimodal image-point cloud sensors, point cloud registration techniques face significant challenges in scenarios characterized by weak texture, sparse geometry, limited overlap, and strong noise interference. In this paper, we present a tightly-coupled visual-geometric feature fusion framework to overcome these limitations, thereby enhancing the robustness and accuracy of registration in challenging scenarios. A density-guided feature sampling method based on radiation field is proposed to address the non-uniform sampling issue inherent in single-sensor vulnerable scenarios. Then, an adaptive weighting strategy for tight visual-geometric feature coupling is introduced to improve performance in scenes with weak texture and geometry. Finally, a visual and geometric fusion correspondence sampling method based on maximal cliques is proposed to enhance matching performance in scenarios with limited overlap and strong noise interference. Notably, the proposed framework can serve as a plug-in to improve the performance of visual and geometric fusion registration algorithms, and the feature detectors used within the framework can be replaced by any feature descriptor-based feature detection method. The proposed method enables multimodal image-point cloud sensors to achieve robust registration in various extreme scenarios, overcoming the potential registration failures inherent in conventional approaches. Experimental results demonstrated that under challenging scenarios, the proposed method improved the inlier ratios of features by 8.37 %, reduced rotational errors by 78.85 %, and decreased translational errors by 85.19 % compared to other methods. This advancement establishes a high-precision point cloud registration framework for large-scale scene reconstruction, exhibiting both robustness and metrological superiority.</div></div>","PeriodicalId":19511,"journal":{"name":"Optics and Laser Technology","volume":"192 ","pages":"Article 113917"},"PeriodicalIF":5.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

Mechanisms of transverse hot crack formation during laser welding of high-strength aluminum alloys at high welding speeds 高强度铝合金高速激光焊接过程中横向热裂纹形成机理

IF 5 2区物理与天体物理

Optics and Laser Technology Pub Date : 2025-09-17 DOI: 10.1016/j.optlastec.2025.113898

Johannes Michel, Jonas Wagner, Frauke Holder, Felix Zaiß, Christian Hagenlocher, Thomas Graf

{"title":"Mechanisms of transverse hot crack formation during laser welding of high-strength aluminum alloys at high welding speeds","authors":"Johannes Michel, Jonas Wagner, Frauke Holder, Felix Zaiß, Christian Hagenlocher, Thomas Graf","doi":"10.1016/j.optlastec.2025.113898","DOIUrl":"10.1016/j.optlastec.2025.113898","url":null,"abstract":"<div><div>High-strength aluminum alloys provide favorable material properties for components in modern battery systems, such as battery trays used in electromobility applications. However, laser welding of high-strength aluminum alloys at high welding speeds may result in the formation of transverse hot cracks in the weld seam, potentially causing component failure due to leakage. To determine strategies to avoid transverse hot cracks, the influence of the welding speed during full-penetration laser welding is analyzed both experimentally and theoretically using numerical simulations of the temperature field and the fluid flow. A metallographic analysis of the welded samples showed an increase in the number of transverse hot cracks with increasing welding speeds. The results revealed that a major mechanism for the formation of transverse hot cracks at high welding speeds is a significant reduction of the static pressure at the side of the melt pool, which impairs liquid feeding into the intergranular region. These findings provide fundamental knowledge for the development of optimization strategies to reduce the formation of transverse hot cracks at high welding speeds.</div></div>","PeriodicalId":19511,"journal":{"name":"Optics and Laser Technology","volume":"192 ","pages":"Article 113898"},"PeriodicalIF":5.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0

A review on laser-induced forward transfer in digital additive manufacturing 数字增材制造中激光诱导前向转移研究进展

IF 5 2区物理与天体物理

Optics and Laser Technology Pub Date : 2025-09-17 DOI: 10.1016/j.optlastec.2025.113914

Xianliang Huang , Mulin Li , Qianxi Yin , Xiaoting Wang , Rongrong Xu , Teng Ma , Ziyi Chen , Jun Chen , Jiancheng Lai

引用次数: 0

3D point cloud damage detection for automating metal repair processes through additive manufacturing 通过增材制造自动化金属修复过程的3D点云损伤检测

IF 5 2区物理与天体物理

Optics and Laser Technology Pub Date : 2025-09-17 DOI: 10.1016/j.optlastec.2025.113904

Miguel O. da Cruz , Daniel Afonso , Miguel Oliveira

{"title":"3D point cloud damage detection for automating metal repair processes through additive manufacturing","authors":"Miguel O. da Cruz , Daniel Afonso , Miguel Oliveira","doi":"10.1016/j.optlastec.2025.113904","DOIUrl":"10.1016/j.optlastec.2025.113904","url":null,"abstract":"<div><div>Damage detection in point clouds is a critical step for automating systems of metal component repair through additive manufacturing. However, current approaches face challenges due to the variability in part geometries and the diversity of damage types. This paper presents a novel damage detection algorithm that adapts to variations in damage location, geometry, and volume through a parameter-driven approach based on plane segmentation and clustering tasks. A synthesized dataset was generated for the validation, with ground truth established using efficient Boolean comparisons combining voxelization with spatial data structures. To optimize the performance of the algorithm, a Design of Experiments was conducted, analyzing parameter influences and guiding the development of optimal detection models. This approach demonstrated a remarkable performance across a wide range of complex damage scenarios, achieving higher precision, recall, and F1 scores than existing methods. The optimized version further enhances recall with minimal impact on precision, ensuring robust and balanced detection capabilities. The approach was also validated in a case study, demonstrating its operational reliability under realistic conditions. This work offers a generalizable solution for effective damage detection, setting a strong foundation for future advancements in automated repair systems.</div></div>","PeriodicalId":19511,"journal":{"name":"Optics and Laser Technology","volume":"192 ","pages":"Article 113904"},"PeriodicalIF":5.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

引用次数: 0