Optics and Lasers in Engineering最新文献

In the simplification, a light field is a four-dimensional (4D) function, and light field reconstruction aims to recover this 4D function from a three-dimensional (3D) focal stack, so it is a seriously ill-posed reconstruction problem from incomplete projection data. Based on the known 3D data of the focal stack in the frequency domain, we introduce a 3D assumption for the light field and derive an analytical reconstruction formula of the light field with an infinite depth range ρ. Subsequently, we establish the filtered back projection (FBP) algorithm to reconstruct the light field from the focal stack. Under certain assumptions concerning the light field and window functions, we prove the convergence of our proposed method at any continuous point. Since in actual data sampling scenarios, the light field is reconstructed only by a small number of focal stacks, a deconvolution algorithm is introduced based on the FBP algorithm to further enhance quality, which is called the filtered back projection-deconvolution (FBP-D) method. Our experimental results demonstrate the superiority of the proposed algorithm compared to the FBP method and other existing methods. Notably, the algorithm exhibits enhanced performance when employing a smooth boundary window and a larger depth range ρ.

Digital holographic microscopy (DHM) is emerged as a promising quantitative phase-contrast imaging tool for full complex wavefront reconstruction of micron-sized bio-samples. The technique covers the dynamics investigation ranging in scales from sub-cellular to tissue and from milliseconds to hours. Recent advances of DHM lie in the configuration and numerical development of the method and making it more feasible for the users without optical expertise. In this paper, we aim to propose a low-cost and portable add-on module for DHM, which can be mounted on either the ocular or camera port of a conventional microscope and easily turn it to a multi-modal bright-field and DHM imaging tool. The module works based on the off-axis, common-path geometry using a single Fresnel biprism in the detection path of the microscope. This configuration enables a compact and cost-effective solution for point of care applications and in field measurements. The feasibility and efficiency of the device have been confirmed through several morphological investigations on biological specimens and the sub-nanometer phase stability enables the measurement of cell dynamics and phenotypic changes such as motility, growth, differentiation and membrane oscillations.

In pupil detection within the visible light spectrum, intensity information serves as a carrier for capturing the reflective characteristics of images. When the reflectance of the pupil and its adjacent iris is similar, effectively distinguishing between them becomes challenging. Polarization provides additional information sensitive to the physical and chemical properties of objects, aiding in overcoming this problem. In the polarimetric pupil detection method, the transmission process of polarized light in the human eye model is theoretically analyzed. Arbitrary orthogonal polarization channels are utilized instead of intensity to describe the collected image, facilitating the extraction of polarization information corresponding to each channel. Experimental validation of the proposed method was conducted using active polarization illumination imaging experiments. The experimental results verify that the polarimetric pupil detection method could not only suppress the scatter noise but also be capable of obtaining a combination of intensity and polarization information. Moreover, exploiting the distinctions in depolarization characteristics among biological tissues can substantially improve their contrast.The research findings presented in this article provide insights into enhancing imaging methods for existing pupil detection schemes.

In this paper, moiré tomography is applied to measure the spatial velocity distribution of thermal wind field. To verify the feasibility of our method, three sets of experiments are carried out, each lasting for 5 min. And then, its spatial distribution is obtained based on the theoretical relation between the refractive index extracted from moiré fringes and the wind velocity. Finally, some validation is performed for the reliability and accuracy of the method. The radial distribution of wind velocity matches well with those estimated results based on a reported theoretical model. Besides, the general trend of wind velocity values at different times of moiré tomography measurement is almost consistent with those recorded by the anemometer, and the relative error between them maintains within 3 %. In further, some reasonable analysis of the factors contributing to error is provided. In a word, this paper demonstrates that moiré tomography has the potential application to offer a feasible means for the spatial measurement of wind velocity.

In order to carry out detailed research on focusing of liquid lens in negative optical power with simple structure, a double-liquid negative lens based on flat electrode is proposed. By adjusting voltage applied to indium tin oxide (ITO) conductive glass plates, the interface between glycerol and silicone oil can be changed to tune the focal length. With COMSOL, MATLAB and Zemax softwares, an optical model of the double-liquid negative lens based on flat electrode is established, its focal length at different voltages is simulated and analyzed, and it is found that when the flat exists with a small tilt (1°∼4°), the parallelism of the flat electrode has little influence on the focal length. In addition, through device fabrication and experimental analysis of this double-liquid negative lens, the focal length of the lens changes from -40.21622 mm to -24.2088 mm when operating voltage is 0V-320 V, which is basically consistent with the simulation results. And the maximum resolution of the proposed liquid lens can reach 71.838lp/mm. A lens with negative focal length holds great promise in diverse applications such as endoscopes, holographic imaging and adaptive optics.

Optical measurement methods for surface topography offer the advantages of high accuracy, rapid measurement, and non-destructiveness. Each method has its own suitable application scenarios. Among them, focus variation microscopy is extensively employed in precision manufacturing, aerospace, and medical industries due to its ability to measure rough and large slopes surfaces. However, since the measurement depends on local grayscale differences between focused and blurred images, it cannot measure surfaces with low reflectivity or insufficient texture information. In this work, we propose an active illumination mode for focus variation method that utilizes a digital micromirror device (DMD) to generate a checkerboard pattern. This method introduces additional texture information, resulting in a usable local gradient of image grayscale. Additionally, we analyze the selection criteria for the checkerboard pattern parameters, including the period and light-dark ratio. Furthermore, measurements of two standard steps with different heights demonstrate that the measurement repeatability of the proposed method can reach the nanometer level, rendering it suitable for high-precision measurements. More importantly, the measurement noise results indicate significantly superior performance of active illumination mode compared to the uniform illumination mode. Finally, we reconstruct the surface topography of the microchannels in a microfluidic chip through the encapsulation layer, demonstrating the feasibility of the proposed method.

Laser-induced vibration is a promising principle of actuation for its energy conversion from optical to mechanical. The nonlinearity of the optical-thermal-mechanical coupling leads to a narrow drive bandwidth in the high vibration mode and limits its applications to conventional micrometer level. In this study, a mathematical model coupling the photothermal effect and the thermoelastic effect has been derived. The numerical calculation shows that the vibration of the cantilever exhibits chaos, bifurcation and modal interaction as the modulated frequency changes, indicating the potential excitation strategy that we can take advantage of these nonlinear states to enhance the energy efficiency beyond micrometer-scale actuation. We propose a new excitation method to enhance the energy efficiency enabling the generation of millimeter-scale vibrations with a single-point pulsed laser. The nonlinearity of cantilever vibration can be further enhanced by controlling the pulse laser frequency, driving the system from stable state to chaos and bifurcation, which leads to increased amplitude and energy efficiency. Compared to stable state, chaos and bifurcation can amplify the amplitude of the cantilever by 5 to 10 times, respectively, with a maximum amplitude of 0.69 mm and 2.31 mm in experimental validations. This allows the laser induced excitation to offer the potential for widely using in non-destructive testing, precision operations, and driving micro-resonators.

Division-of-aperture polarimetric (DoAP) camera has been widely used to obtain polarization images of scene owing to its feature in simultaneous acquisition of polarization information, real-time measurement and compact system. However, practical applications of DoAP imaging inevitably involve calibrating the camera from several aspects, which is very essential but the related reports are relatively lacking in current research. In this paper, we proposed a systematical and universal calibration scheme for the DoAP camera, which includes the lens distortion correction, the image registration, the polarization channel calibration and the Stokes parameters modification. Accordingly, a software for calibration and imaging processing, which consists of four modules, is designed to collectively facilitate the efficient and accurate execution of all calibration steps. In order to achieve real-time polarimetric imaging, the lens distortion correction and the image registration were done by means of lookup tables. Experimental results by using a full-Stokes DoAP camera we fabricated indicate that, via the lens distortion correction and the image registration, the alignment error between two images with a mean absolute error (MAE) less than 0.16 pixels can be obtained, resulting in the aligned images having an average increase of 64.53 % for the structural similarity index (SSIM) and that of 84.97 % for the peak signal to noise ratio (PSNR), respectively; and further via the polarization channel calibration and the Stokes parameters modification, the MAE of 0.0146 for the degree of polarization (DoP) and that of 0.3544° for the angle of polarization (AoP) are obtained, respectively. This proposed calibration scheme for DoAP camera is systematic, automatic and robust, which is benefit of improving the polarization detection accuracy, enhancing the camera calibration efficiency and thus promoting its polarimetric imaging performance.

Deep learning is expected to overcome the intractable challenges that traditional digital image correlation (DIC) confronts in the measurement of extremely complex deformation fields with severe spatial variation. The recently developed DIC methods based on convolutional neural network (CNN) achieved notable success in tackling highly localized deformation. This paper introduces an innovative DIC method based on Transformer (named DICTr), which is found to outperform its CNN-based counterparts. Different from CNN-based DIC that try to establish the relationship between the changes in grayscale values and the displacements through regression, DICTr reformulates the problem back to the image registration driven by feature matching. The displacement field is estimated in a coarse-to-fine way through matching the features enhanced by a sophisticatedly designed Transformer encoder. In experimental verification, DICTr demonstrates outstanding accuracy and robustness to measure complex displacement fields, and balances well the spatial resolution and measurement resolution.

For non-contact deformation testing, digital holographic interferometry is a prominent optical technique where the first and second order interference phase derivatives directly embed information about the strain and curvature distributions of a deformed object. Hence, reliable extraction of multiple order phase derivatives is of great practical significance; however, this problem is marred by several challenges such as the need of multiple differentiation operations, complex shearing operations and performance degradation due to noise. In this paper, we introduce a deep learning approach for the direct and simultaneous estimation of first and second order phase derivatives in digital holographic interferometry. Our method's performance is demonstrated via rigorous numerical simulations exhibiting wide range of additive white Gaussian noise and speckle noise. Moreover, we substantiate the practical efficacy of our proposed method for processing deformation fringes acquired via digital holographic interferometry.