Optics and Lasers in Engineering最新文献

{"title":"A low-cost fiber-optic temperature sensor utilizing integrated sensing and leaky mode specklegram analysis","authors":"Yin Liu ,&nbsp;Ju Wang ,&nbsp;Qilei Fang ,&nbsp;Kai Zhang ,&nbsp;Yuzhuo Li ,&nbsp;Yifan Men ,&nbsp;Man Yu ,&nbsp;Hong Fan ,&nbsp;Tianyun Lan ,&nbsp;Jia You ,&nbsp;Xisheng Li ,&nbsp;Hongbing Chen","doi":"10.1016/j.optlaseng.2025.109371","DOIUrl":"10.1016/j.optlaseng.2025.109371","url":null,"abstract":"<div><div>Fiber-optic sensors are highly sensitive to physical, chemical, and biological variations, making them essential for precision measurements in complex environments. Achieving cost-effectiveness, miniaturization, and scalability simultaneously, however, remains challenging. To address this, an integrated fiber-optic sensing approach is presented. A tapered fiber segment is employed to generate leaky-mode speckle patterns, with geometric parameters and a thermosensitive coating optimized to modulate leakage intensity and spatial distribution in response to temperature. Experimental results confirm a direct correlation between specklegram features and temperature across 5 °C–80 °C. Temperature inversion is performed using a deep learning model based on the Xception convolutional neural network. The modular system design allows adaptation to other sensing modalities through material or detector modification while preserving core functionality. This approach overcomes traditional trade-offs between cost, size, and scalability, demonstrating robust and versatile performance for practical applications.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":"196 ","pages":"Article 109371"},"PeriodicalIF":3.7,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145222967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wavelength by design: A comprehensive review of spectral diffractive optical elements","authors":"Nikolay L. Kazanskiy ,&nbsp;Svetlana N. Khonina","doi":"10.1016/j.optlaseng.2025.109374","DOIUrl":"10.1016/j.optlaseng.2025.109374","url":null,"abstract":"<div><div>Spectral diffractive optical elements (DOEs) have emerged as powerful tools for wavelength-selective manipulation of light in compact, planar formats. This review provides a comprehensive overview of the principles, design methodologies, fabrication techniques, and application landscapes of spectral DOEs. Emphasizing their spectral sensitivity and phase-engineering capabilities, we examine how DOEs enable functionalities such as dispersion control, wavelength multiplexing, chromatic aberration correction, and hyperspectral imaging. Key design strategies including analytical models, iterative optimization, and inverse design methods are discussed alongside advancements in fabrication approaches such as grayscale lithography, nanoimprint lithography, and two-photon polymerization. Material platforms from fused silica and silicon to polymers are evaluated for their spectral, mechanical, and environmental performance. Application domains span imaging systems, optical communications, spectroscopy, AR/VR displays, and solar energy harvesting. We also explore emerging directions such as multilayer and 3D diffractive structures, tunable DOEs, metasurface-enhanced hybrids, and AI-driven design automation. While spectral DOEs offer significant advantages in scalability, functionality, and integration, challenges remain in broadband efficiency, fabrication precision, and polarization control. This review highlights current limitations and identifies promising pathways for overcoming them, positioning spectral DOEs as critical components in next-generation photonic systems.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":"196 ","pages":"Article 109374"},"PeriodicalIF":3.7,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A color polarization demosaicing network based on sampling fusion and high-frequency information perception","authors":"Yubo Zheng,&nbsp;Xiangyue Zhang,&nbsp;Junlin Li,&nbsp;Zhixin Dong,&nbsp;Chengdong Wu","doi":"10.1016/j.optlaseng.2025.109361","DOIUrl":"10.1016/j.optlaseng.2025.109361","url":null,"abstract":"<div><div>The color polarization filter array (CPFA) camera is widely used in various polarization-based computer vision tasks due to its ability to simultaneously capture both color and polarization information. However, due to the limitations of the CPFA's superpixel structure and the entanglement of information within the color and polarization channels, the demosaicking problem becomes highly ill-posed. Most existing methods only rely on a single sampling approach and ignore high-frequency polarization information, which often lead to color reconstruction errors and edge artifacts, thus affecting the quality of degree of linear polarization and angle of polarization. In this paper, a Color-polarization demosaicing network based on sampling fusion and high-frequency information perception is proposed to decouple and reconstruct color and polarization information. During low-resolution image sampling, the advantages of traditional interpolation and deep learning methods are integrated through a self-guidance residual compensation interpolation module, which provides richer cues for subsequent refinement. In the polarization reconstruction stage, a Stokes activation sub-network is introduced to leverage the high-frequency signals encoded in the Stokes vectors, thereby enhancing edge and detail recovery in the polarization intensity domain. Furthermore, a color-polarization weighted loss function is designed to jointly optimize the network by complementing information across different dimensions. Experimental results demonstrate that the proposed method achieves state-of-the-art performance in reconstructing polarization parameters and visualization. The accurately reconstructed polarization parameters provide a solid and high-quality guidance for subsequent tasks.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":"195 ","pages":"Article 109361"},"PeriodicalIF":3.7,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep neural network for processing single fringe patterns: Applications in phase recovery and denoising","authors":"Jesús Villa ,&nbsp;Gamaliel Moreno ,&nbsp;Ismael de la Rosa ,&nbsp;Jorge Luis Flores","doi":"10.1016/j.optlaseng.2025.109348","DOIUrl":"10.1016/j.optlaseng.2025.109348","url":null,"abstract":"<div><div>This paper presents a Deep Neural Network Fringe Processor (DNNFP) for unified estimation of fringe orientation and frequency from single fringe patterns. Unlike conventional convolutional neural network (CNN) approaches that require prior image filtering and fixed input dimensions, our method processes raw fringe patterns of arbitrary size through a single neural network architecture. The DNNFP combines computational efficiency with operational simplicity, enabling consistent processing across diverse noise conditions without manual parameter tuning.</div><div>The proposed DNNFP analyzes local pixel neighborhoods to simultaneously extract orientation and frequency parameters, eliminating preprocessing steps and specialized algorithms. Experimental results demonstrate the method's practical utility in handling real-world fringe patterns, while qualitative analysis highlights advantages over CNN-based approaches in architectural simplicity and operational flexibility.</div><div>Key advantages include: (1) Elimination of preprocessing steps (denoising and reshaping) required by CNN methods, (2) single-network estimation of both orientation and frequency, and (3) parameter-free operation suitable for practical implementation. These features make the DNNFP particularly valuable for optical metrology applications where accurate phase recovery from single fringe patterns is essential. The method establishes a new framework for fringe pattern analysis that combines deep learning accuracy with practical usability.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":"195 ","pages":"Article 109348"},"PeriodicalIF":3.7,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FRFusion: A deep fusion framework for infrared and visible images based on fast fourier transform and retinex model","authors":"Zhen Pei ,&nbsp;Jinbo Lu ,&nbsp;Jinling Chen ,&nbsp;Yongliang Qian ,&nbsp;Lihua Fan ,&nbsp;Hongyan Wang","doi":"10.1016/j.optlaseng.2025.109362","DOIUrl":"10.1016/j.optlaseng.2025.109362","url":null,"abstract":"<div><div>Infrared and visible image fusion exploits the complementary characteristics of both modalities to produce a richer and more visually enhanced image. However, most existing methods primarily focus on well-lit conditions and tend to overlook texture and contrast degradation in low-light environments. Furthermore, these approaches often neglect frequency domain information during feature extraction. We propose a network called FRFusion for fusing infrared and visible images in low-light environments to address the aforementioned challenges. Firstly, based on the Retinex model, we designed encoders with different structures to decompose visible images into reflection and illumination components. During this process, we introduced a feature adjustment module (<span><math><mrow><mi>F</mi><mi>A</mi><mi>M</mi></mrow></math></span>) to enable the model to simultaneously extract information from the input image in spatial and frequency domains. It is worth noting that the extraction of infrared features pertains to the encoder structure of the reflection components of visible images. Secondly, in the feature fusion stage, we introduced the dual attention feature fusion module (<span><math><mrow><mi>D</mi><mi>A</mi><mi>F</mi><mi>F</mi><mi>M</mi></mrow></math></span>) to fully integrate the global and local features of infrared and visible images, thereby achieving a more comprehensive synthesis of complementary information. Finally, we propose a brightness adaptive network (<span><math><mrow><mi>B</mi><mi>A</mi><mi>N</mi></mrow></math></span>) for the illumination component, which restores the brightness information of the fused image by adaptively adjusting the brightness features. Experimental results on three public datasets demonstrate that our method excels in both visual quality and evaluation metrics.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":"195 ","pages":"Article 109362"},"PeriodicalIF":3.7,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Laser generated surface acoustic wave using diffractive optical elements","authors":"Yufei Chu ,&nbsp;Yoganandh Madhuranthakam ,&nbsp;Zebadiah Miles ,&nbsp;Farzia Karim ,&nbsp;Anish Poudel ,&nbsp;Yiming Deng ,&nbsp;Ming Han ,&nbsp;Sunil Kishore Chakrapani","doi":"10.1016/j.optlaseng.2025.109325","DOIUrl":"10.1016/j.optlaseng.2025.109325","url":null,"abstract":"<div><div>Laser-induced generation of surface acoustic waves (SAW) has emerged as a highly promising method for ultrasonic testing due to its non-contact nature and elimination of the need for physical coupling, making it suitable for a wide range of applications. However, a major limitation in current research is frequency dispersion, which complicates signal interpretation and reduces the accuracy of material characterization. This article explores the use of a beam splitter-based diffractive optical element (DOE) to optimize SAW generation and address this issue. A single DOE was used to generate a multipoint laser source array, and a series of lenses were utilized to reshape these into point and line sources of different dimensions. The comb-like design was based on the SAW wavelength. The influence of the number of sources and the types of sources, i.e., line vs. point, on the SAW generation was investigated. Additionally, we analyze how different line-source lengths influence SAW generation. Theoretical models were first developed to understand the use of DOE and the effect of source width and frequency on SAW propagation. The optical models were further used to design the experiments and study the influence of various parameters, including laser source energy. Compared to the point source, the line sources were observed to result in a significantly higher temporal and spectral response with a narrower bandwidth of the SAW wave. The results suggest that the comb-like arrangement increases the generation efficiency of the SAW wave.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":"195 ","pages":"Article 109325"},"PeriodicalIF":3.7,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"N-step self-calibrated generalized amplitude-phase-shifting interferometry","authors":"Carlos Augusto Flores-Meneses ,&nbsp;Maximino Avendaño-Alejo ,&nbsp;Cruz Meneses-Fabian","doi":"10.1016/j.optlaseng.2025.109343","DOIUrl":"10.1016/j.optlaseng.2025.109343","url":null,"abstract":"<div><div>We present a precise, efficient, and non-iterative self-calibrated method for complex amplitude retrieval (both amplitude and phase), generalized for an arbitrary number N of phase shifts in phase-shifting interferometry (PSI). In conventional PSI, only the wavefront phase is retrieved, either by performing synchronous detection—using equal phase steps—or asynchronous detection—using unequal but known phase steps. In contrast, the proposed approach enables the simultaneous recovery of the wavefront phase, the reference and probe amplitudes, and the unknown phase steps, without ambiguity and for any number of interferograms, thus allowing a complete reconstruction of the optical field. The technique is first validated through numerical simulations, showing that all optical field parameters can be accurately recovered and that the deviation from the theoretical values is practically zero. Additionally, a comprehensive noise analysis is performed by simulating typical experimental error sources, which are analyzed individually and collectively to emulate real acquisition conditions. The method proves to be robust even under adverse conditions, maintaining high reconstruction accuracy. Experimentally, the method is implemented in a double-aperture common-path interferometer (DACPI) adapted for polarization modulation. Results are presented for up to ten interferograms with arbitrary phase shifts, demonstrating that all parameters can be recovered with high precision and low error. Furthermore, the experimental results show excellent agreement with the numerical noise analysis, validating the reliability and practical applicability of the proposed self-calibrating approach.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":"195 ","pages":"Article 109343"},"PeriodicalIF":3.7,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SMF temperature sensor with PDMS coated for respiratory monitoring","authors":"Pingbang Huang ,&nbsp;Wenmi Li ,&nbsp;Yuxin Liu ,&nbsp;Xiaoyun Tang ,&nbsp;Yaxun Zhang ,&nbsp;Zhihai Liu ,&nbsp;Yu Zhang ,&nbsp;Libo Yuan","doi":"10.1016/j.optlaseng.2025.109353","DOIUrl":"10.1016/j.optlaseng.2025.109353","url":null,"abstract":"<div><div>An optical fiber Mach–Zehnder interferometer temperature sensor based on Polydimethylsiloxane (PDMS) sensitization is proposed and implemented. The sensor is composed of droplet-shaped single mode fiber (SMF) coated with PDMS, which utilizes the high negative thermo-optic coefficient and high thermal expansion coefficient of PDMS to enhance the sensitivity of the temperature sensor. The measurement range of this sensor is 15 °C to 85 °C, with a maximum temperature sensitivity of 0.3107nm/ °C, which is 8-time higher than the temperature sensitivity of a droplet-shaped SMF sensor without PDMS coating. The proposed temperature sensor is combined with a wearable oxygen mask to monitor the real-time respiratory status of the human body. This combination has the potential to be applied in the manufacturing of wearable medical or bio-detection devices. The sensor has the advantages of simple fabrication, stable structure, good repeatability, high time stability, and insensitivity to humidity.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":"195 ","pages":"Article 109353"},"PeriodicalIF":3.7,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Underwater image enhancement via standard deviation reconstruction, dynamic sigmoid mapping and gradient-aware enhancement","authors":"Xinwen Wan ,&nbsp;Qiao Wei ,&nbsp;Xinyi Xu ,&nbsp;Jinqin Zhong ,&nbsp;Weidong Zhang ,&nbsp;Ling Shen ,&nbsp;Wei Ju ,&nbsp;Zheng Liang","doi":"10.1016/j.optlaseng.2025.109339","DOIUrl":"10.1016/j.optlaseng.2025.109339","url":null,"abstract":"<div><div>Underwater images collected by optical electronic devices often suffer from color cast and low contrast due to the wavelength-dependent attenuation of light propagation. To deal with these challenging issues, this paper proposes an underwater image enhancement method based on an adaptive standard deviation reconstruction, a dynamic sigmoid mapping and a gradient-aware contrast enhancement, called SDGE. Concretely, we first study the influence of the standard deviation of Gaussian kernel on the color restoration results regarding different underwater images, and find it has a marked impact on colors. Meanwhile, we rebuild the standard deviation of Gaussian kernel based on the attenuation characteristics of each image, which enables us to adaptively adjust the smoothness degree of different images, thereby eliminating the color veil and preserving the significant structure and texture. Then, we utilize the maximum value of each channel to design diverse sigmoid functions, and dynamically simulate the nonlinear mapping of human color perception, achieving the correction of dynamic range and color distortion. Finally, we use an histogram equalization method to optimize the structure and design a gradient-aware coefficient to amplify the detail for producing the enhanced image. Broad experiments on four underwater image datasets demonstrate that the enhancement methods with our SDGE produce the considerable results in both qualitative and quantitative evaluations, i.e., our method achieves the best performance on the UCCS and UIQS datasets regarding all quantitative metrics, and our method at least increases by 95.67%, 76.74%, 1.28%, 9.94% and 3.75% compared with the second-best method in terms of the <em>e</em>, <span><math><mover><mrow><mi>r</mi></mrow><mrow><mo>¯</mo></mrow></mover></math></span>, Entropy, UIQM and UCIQE values, respectively. These competitive datas indicate our method has the excellent performance in enhancing the clear visibility, correcting the natural appearance and highlighting the details. Moreover, our method provides superior generalization ability for enhancing complex remote sensing images.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":"195 ","pages":"Article 109339"},"PeriodicalIF":3.7,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145104529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction methods of deep virtual datasets for single-plane diffractive elements","authors":"Xian Zhang,&nbsp;Mingxu Piao,&nbsp;Junsong Wang,&nbsp;Zonglin Liang,&nbsp;Bo Zhang","doi":"10.1016/j.optlaseng.2025.109346","DOIUrl":"10.1016/j.optlaseng.2025.109346","url":null,"abstract":"<div><div>The miniaturization and simplification of optical imaging systems have become critical demands in modern optics, yet conventional refractive optics remain bulky. The Single-Plane Diffractive Optical Element (SPDOE) enables image formation with a single optical component and features simpler microstructural fabrication compared to other advanced elements. However, owing to its distinct diffractive nature, the SPDOE inevitably introduces aberration-induced blur and diffraction-related background blurring in the imaging process. In this study, a virtual dataset construction method capable of accurately characterizing the degradation features of the SPDOE was proposed. Combined with a simplified neural network, high-quality real-time imaging was ultimately achieved. The aberration-induced image degradation was simulated by convolving the full-field point spread function (PSF) with the target image, while the diffraction-related background blur was modeled based on the proposed PSF degradation method derived from diffraction efficiency. An SPDOE with an f-number of 5 and a focal length of 50 mm was fabricated, operating within the visible wavelength range of 486–656 nm. Experimental results demonstrate that a structural similarity index (SSIM) of up to 0.9012 was achieved between the synthetic degraded images constructed using this method and the actual SPDOE captured images. A peak signal-to-noise ratio(PSNR) of 28.1 dB was obtained from tests conducted on real captured images, the accuracy of the constructed method was quantitatively validated. Compared with conventional deconvolution based on PSF models, the proposed deep learning approach achieved over fivefold improvement in real-time performance. This method addresses the limitations of small-sample SPDOE datasets, significantly reduces image acquisition and reconstruction time, and eases pixel alignment, providing a theoretical foundation for high-quality real-time imaging with SPDOE.</div></div>","PeriodicalId":49719,"journal":{"name":"Optics and Lasers in Engineering","volume":"195 ","pages":"Article 109346"},"PeriodicalIF":3.7,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}