ABSTRACT
As industrial and scientific advancements continue, the demand for precise measurement of three-dimensional (3D) shapes and surfaces is steadily increasing. However, accurate 3D measurement of certain surfaces, especially those with varying reflectivities, has always been a challenging issue. Multi-exposure fusion methods have shown stable, high-quality measurement results, but the selection of parameters for these methods has largely been based on experience. To address this issue, this paper has improved the multi-exposure fusion method and introduced a guided approach for parameter selection, significantly enhancing the completeness of measurement results. Additionally, a comparative model is developed to experimentally validate the specific impacts of Gaussian window variance, optimal grayscale range, and attenuation factor variance on the integrity of 3D reconstruction. The experimental results demonstrate that under the guidance of the parameter adjustment method proposed in this paper, the multi-exposure fusion for measuring the 3D topography of high-dynamic surfaces improves the restoration coverage from the original 86% (bright areas) and 50% (dark areas) to over 99%. This provides a selection strategy for parameter adjustment guidance in precise measurements based on the multi-exposure method.
ABSTRACT
In single-shot speckle projection profilometry (SSPP), the projected speckle inevitably undergoes changes in shape and size due to variations such as viewing angles, complex surface modulations of the test object and different projection ratios. These variations introduce randomness and unpredictability to the speckle features, resulting in erroneous or missing feature extraction and subsequently degrading 3D reconstruction accuracy across the tested surface. This work strives to explore the relationship between speckle size variations and feature extraction, and address the issue solely from the perspective of network design by leveraging specific variations in speckle size without expanding the training set. Based on the analysis of the relationship between speckle size variations and feature extraction, we introduce the NMSCANet, enabling the extraction of multi-scale speckle features. Multi-scale spatial attention is employed to enhance the perception of complex and varying speckle features in space, allowing comprehensive feature extraction across different scales. Channel attention is also employed to selectively highlight the most important and representative feature channels in each image, which is able to enhance the detection capability of high-frequency 3D surface profiles. Especially, a real binocular 3D measurement system and its digital twin with the same calibration parameters are established. Experimental results imply that NMSCANet can also exhibit more than 8 times the point cloud reconstruction stability (Std) on the testing set, and the smallest change range in terms of Mean~dis (0.0614 mm - 0.4066 mm) and Std (0.0768 mm - 0.7367 mm) when measuring a standard sphere and plane compared to other methods, faced with the speckle size changes, meanwhile NMSCANet boosts the disparity matching accuracy (EPE) by over 35% while reducing the matching error (N-PER) by over 62%. Ablation studies and validity experiments collectively substantiate that our proposed modules and constructed network have made significant advancements in enhancing network accuracy and robustness against speckle variations.
ABSTRACT
The three-dimensional (3D) measurement task of complex microstructures holds paramount significance in the domains of precision manufacturing and inspection. The calibration of the 3D system heavily determines the final reconstruction accuracy. The widely adopted system calibration method is phase-height mapping (PHM) and stereo vision (SV) based. The former can be applied directly to the calculation without considering the imaging model of the system, but it relies on highly precise and expensive translation stages or standard blocks. The latter's accuracy cannot be guaranteed because it is difficult to accurately calibrate the projector. In this paper, we establish an optically coupled microscopic fringe projection profilometry system that consists of a Scheimpflug pinhole projector and a super-low distortion bi-telecentric camera. We introduce a simplified 3D system calibration approach that combines phase modulation transfer and ray propagation. Our method enables the simultaneous calibration of the system, including the calibration of the projector, camera, and the phase to a 3D coordinates relationship, using only a 2D target. The calibrated projector's external parameters are used to obtain the target's complete poses, and then the direct mapping coefficients of the phase to the 3D coordinates can be obtained through the optical geometry structure and phase labels. Comparable experiments verify the feasibility of the proposed method.
ABSTRACT
Extreme climate events have increased in frequency and severity under the background of climate change, with vegetation growth exhibiting a sensitive response to them. By assimilating GIMMS NDVI and MODIS NDVI using the Residual Network, we obtained a long time series and high resolution NDVI dataset of the Yellow River Basin (YRB). The dataset was utilized for examining the spatiotemporal variability of NDVI and analyzing the response of vegetation cover to climate extremes with meteorological data. Our findings reveal the following: (1) A significant rise in NDVI was seen in the YRB, displaying a mean growth rate of 0.019/10a (p < 0.001). However, seasonal differences exist. The mean NDVI of multi-year declines from southeast to northwest, while the overall trend of vegetation cover improves. (2) The NDVI response to extreme temperature exhibits noticeable spatiotemporal differences. Daytime extreme high temperature in the northern YRB is negatively correlated with NDVI, while they are positively correlated in the lower YRB and the southern part of the middle YRB. Nighttime extreme high temperature exhibits a positive correlation with NDVI. Overall, NDVI displays a stronger response to extreme precipitation than to extreme temperature, with a negative correlation with CWD and a positive correlation with PRCPTOT. (3) The NDVI demonstrates a lagged response to climate extremes in the YRB, with a greater lag in response to extreme temperature than extreme precipitation. The research findings can provide scientific support for the future management and planning of vegetation in the YRB, as well as contribute to the promotion of ecological environment regulation and sustainable development.
ABSTRACT
Perovskite/silicon tandem solar cells are promising avenues for achieving high-performance photovoltaics with low costs. However, the highest certified efficiency of perovskite/silicon tandem devices based on economically matured silicon heterojunction technology (SHJ) with fully textured wafer is only 25.2% due to incompatibility between the limitation of fabrication technology which is not compatible with the production-line silicon wafer. Here, a molecular-level nanotechnology is developed by designing NiOx /2PACz ([2-(9H-carbazol-9-yl) ethyl]phosphonic acid) as an ultrathin hybrid hole transport layer (HTL) above indium tin oxide (ITO) recombination junction, to serve as a vital pivot for achieving a conformal deposition of high-quality perovskite layer on top. The NiOx interlayer facilitates a uniform self-assembly of 2PACz molecules onto the fully textured surface, thus avoiding direct contact between ITO and perovskite top-cell for a minimal shunt loss. As a result of such interfacial engineering, the fully textured perovskite/silicon tandem cells obtain a certified efficiency of 28.84% on a 1.2-cm2 masked area, which is the highest performance to date based on the fully textured, production-line compatible SHJ. This work advances commercially promising photovoltaics with high performance and low costs by adopting a meticulously designed HTL/perovskite interface.
