Plant litter loss exacerbates drought influences on grasslands.

Plant litter is known to affect soil, community, and ecosystem properties. However, we know little about the capacity of litter to modulate grassland responses to climate change. Using a 7-yr litter removal experiment in a semiarid grassland, here we examined how litter removal interacts with a 2-yr drought to affect soil environments, plant community composition, and ecosystem function. Litter loss exacerbates the negative impacts of drought on grasslands. Litter removal increased soil temperature but reduced soil moisture and nitrogen mineralization, which substantially increased the negative impacts of drought on primary productivity and the abundance of perennial rhizomatous graminoids. Moreover, complete litter removal shifted plant community composition from grass-dominated to forb-dominated and reduced species and functional group asynchrony, resulting in lower ecosystem temporal stability. Our results suggest that ecological processes that lead to reduction in litter, such as burning, grazing, and haying, may render ecosystems more vulnerable and impair the capacity of grasslands to withstand drought events.

Simulation framework for fringe projection profilometry using ray tracing and light transport coefficient measurement.

Fringe projection profilometry is widely used in optical metrology, and fringe analysis is important to improve measurement accuracy. However, the fringe images captured by cameras are influenced by many factors, an analytical study of which, to characterize the imaging process, is difficult to perform. We propose a method to accurately simulate the real imaging system in the virtual environment using ray tracing algorithm. The light transport coefficients of the cameras are measured to simulate defocus instead of using Gaussian function. Experimental results show that the proposed method can simulate a physical system in the virtual environment more accurately than the Gaussian function at large defocus condition.

3D shape measurement in the presence of strong interreflections by using single-pixel imaging in a camera-projector system.

Optical 3D shape measurements, such as fringe projection profilometry (FPP), are popular methods for recovering the surfaces of an object. However, traditional FPP cannot be applied to measure regions that contain strong interreflections, resulting in failure in 3D shape measurement. In this study, a method based on single-pixel imaging (SI) is proposed to measure 3D shapes in the presence of interreflections. SI is utilized to separate direct illumination from indirect illumination. Then, the corresponding points between the pixels of a camera and a projector can be obtained through the direct illumination. The 3D shapes of regions with strong interreflections can be reconstructed with the obtained corresponding points based on triangulation. Experimental results demonstrate that the proposed method can be used to separate direct and indirect illumination and measure 3D objects with interreflections.

Paraxial 3D shape measurement using parallel single-pixel imaging.

Three-dimensional (3D) shape measurement with fringe projection technique and vertical scanning setup can alleviate the problem of shadow and occlusion. However, the shape-from-defocus based method suffers from limited sensitivity and low signal-to-noise ratio (SNR), whereas the projection-triangulation based is sensitive to the zero-phase detection. In this paper, we propose paraxial 3D shape measurement using parallel single-pixel imaging (PSI). The depth is encoded in the radial distance to the projector optical center, which is determined by the projection of light transport coefficients (LTCs). The third-order polynomial fitting is used for depth mapping and calibration. Experiments on 5 objects with different materials and textures are conducted, and standards are measured to test the accuracy. The results verified that the proposed method can achieve robust, dense reconstruction with depth accuracy at 20 µm while the root-mean-square error (RMSE) of plane fitting up to 43 µm.

Compressive parallel single-pixel imaging for efficient 3D shape measurement in the presence of strong interreflections by using a sampling Fourier strategy.

We present a compressive parallel single-pixel imaging (cPSI) method, which applies compressive sensing in the context of PSI, to achieve highly efficient light transport coefficients capture and 3D reconstruction in the presence of strong interreflections. A characteristic-based sampling strategy is introduced that has sampling frequencies with high energy and high probability. The characteristic-based sampling strategy is compared with various state-of-the-art sampling strategies, including the square, circular, uniform random, and distance-based sampling strategies. Experimental results demonstrate that the characteristic-based sampling strategy exhibits the best performance, and cPSI can obtain highly accurate 3D shape data in the presence of strong interreflections with high efficiency.

Separation of interreflections based on parallel single-pixel imaging.

Interreflections introduced by points in a scene are not only illuminated by the light source used but also by other points in the scene. Interreflections cause inaccuracy and the failure of 3D recovery and optical measurements. In this research, a novel method for separating interreflections through parallel single-pixel imaging (PSI) is proposed, which can decompose interreflections into 1st bounce light, 2nd bounce light, and a higher order light component. PSI is used in obtaining the light transport coefficients of each camera pixel, and light transport coefficients are used in decomposing the intensity distribution of a projector and the component of interreflections. Results show that the proposed method can separate the interreflections of a real static scene in a concave surface.

Space-variant point spread function measurement and interpolation at any depth based on single-pixel imaging.

Point spread function (PSF) is important for evaluating an optical system and image deblurring. In this paper, we proposed a method to measure space-variant PSF at any depth based on single-pixel imaging (SPI), and we initiated a depth-variant PSF interpolation model. In our method, we regarded space-variant PSF as light transport coefficients from object points to image pixels. By applying SPI to each image pixel to obtain these light transport coefficients at different depths, the PSF of each object point can be extracted. The depth calculation of PSF is based on multi-frequency heterodyne phase-shifting principles and perspective-n-point (PnP) algorithm. In our PSF interpolation model, we interpolated the light transport coefficients from different object points to an image pixel first. We then obtained the interpolated PSF indirectly from the interpolated coefficients. With simple experimental facilities containing a digital camera and a liquid crystal display (LCD) screen to display and capture specific patterns, which relative distance is changed, the proposed method accurately obtained the space-variant PSF at any depth. Without complicated calculation, PSF at a certain depth can be interpolated from the PSF measured data at another depth with our PSF interpolation method. Significant similarities exist between the interpolated PSF and directly measured PSF. Our work is a successful attempt in using SPI to solve traditional optical problems.

High-Accuracy 3-D Sensor for Rivet Inspection Using Fringe Projection Profilometry with Texture Constraint.

Riveted workpieces are widely used in manufacturing; however, current inspection sensors are mainly limited in nondestructive testing and obtaining the high-accuracy dimension automatically is difficult. We developed a 3-D sensor for rivet inspection using fringe projection profilometry (FPP) with texture constraint. We used multi-intensity high dynamic range (HDR) FPP method to address the varying reflectance of the metal surface then utilized an additional constraint calculated from the fused HDR texture to compensate for the artifacts caused by phase mixture around the stepwise edge. By combining the 2-D contours and 3-D FPP data, rivets can be easily segmented, and the edge points can be further refined for diameter measurement. We tested the performance on a sample of riveted aluminum frame and evaluated the accuracy using standard objects. Experiments show that denser 3-D data of a riveted metal workpiece can be acquired with high accuracy. Compared with the traditional FPP method, the diameter measurement accuracy can be improved by 50%.

High-accuracy 3D shape measurement of translucent objects by fringe projection profilometry.

Acquiring complete and accurate 3D shape measurement results of translucent objects by fringe projection profilometry (FPP) is difficult because of the subsurface scattering effect. The phase offset introduces geometric errors, and the degraded image contrast leads to incomplete measurement results and random errors. In this research, a high-accuracy 3D shape measurement method for translucent objects based on phase-shifting FPP is proposed. The relationship between fringe period and phase error is investigated to determine the fringe periods. Random errors are suppressed by temporal noise reduction, and the robustness of multi-frequency heterodyne phase unwrapping is improved by increasing the interval of fringe periods along with temporal noise reduction. Geometric errors are compensated for by projecting multi-frequency fringe patterns to establish the relationship between fringe period and depth offset. Experimental results show that the proposed method can acquire complete measurement results and significantly reduce the overall error for measuring translucent objects.

3D shape measurement of translucent objects based on Fourier single-pixel imaging in projector-camera system.

3D shape measurement by structured light is a popular technique for recovering object surfaces. However, structured light technique assumes that scene points are directly illuminated by the light source(s). Consequently, global illumination effects, such as subsurface scattering in translucent objects, may cause measurement errors in recovered 3D shapes. In this research, we propose a 3D shape measurement method of translucent objects based on Fourier single-pixel imaging (FSI) technique. The 3D shapes of the translucent objects are reconstructed through stereo matching of direct illumination light, which is separated from the surface. Experimental results show that the proposed method can separate the direct illumination light and the subsurface scattering light. The feasibility and accuracy of the method are analyzed, and the qualitative and quantitative results of the method are provided.

SWIR AOTF Imaging Spectrometer Based on Single-pixel Imaging.

An acousto-optic tunable filter (AOTF) is a new type of mono-wavelength generator, and an AOTF imaging spectrometer can obtain spectral images of interest. However, due to the limitation of AOTF aperture and acceptance angle, the light passing through the AOTF imaging spectrometer is weak, especially in the short-wave infrared (SWIR) region. In weak light conditions, the noise of a non-deep cooling mercury cadmium telluride (MCT) detector is high compared to the camera response. Thus, effective spectral images cannot be obtained. In this study, the single-pixel imaging (SPI) technique was applied to the AOTF imaging spectrometer, which can obtain spectral images due to the short-focus lens that collects light into a small area. In our experiment, we proved that the irradiance of a short-focus system is much higher than that of a long-focus system in relation to the AOTF imaging spectrometer. Then, an SPI experimental setup was built to obtain spectral images in which traditional systems cannot obtain. This work provides an efficient way to detect spectral images from 1000 to 2200 nm.

3D shape measurement in the presence of strong interreflections by epipolar imaging and regional fringe projection.

A 3D shape measurement method in the presence of strong interreflections is presented. Traditional optical 3D shape measurement methods such as fringe projection profilometry (FPP) cannot measure regions that contain strong interreflections, which result in 3D shape measurement failure. In the proposed method, epipolar imaging with speckle patterns is utilized to eliminate the effects of interreflections and obtain the initial 3D shape measurement result. Regional fringe projection based on the initial measurement result is further applied to achieve high-accuracy measurement. Experimental results show that the proposed method can measure the regions that contain strong interreflections at a high accuracy.

Projector-defocusing rectification for Fourier single-pixel imaging.

Fourier single-pixel imaging (FSI) is an efficient single-pixel imaging method of obtaining high-quality (resolution/signal-to-noise ratio) 2D images, which projects sinusoid patterns on the object and reconstructs the image through reflected light. The typical system of FSI consists of a single-pixel detector and a digital projector. However, the defocusing of the projector lens blurs the projected patterns, which results in reduced imaging quality. In this work, we propose the projector-defocusing rectification for FSI, which optimizes projector defocusing for the first time. The proposed method rectifies Fourier coefficients using the amplitude ratio between original and defocused patterns, which we can acquire through a controlled experiment on a whiteboard. The enhancement of imaging quality in imperfect circumstances is demonstrated by simulations and experiments.

Defocusing parameter selection strategies based on PSF measurement for square-binary defocusing fringe projection profilometry.

Three-dimensional (3D) shape measurement system with binary defocusing technique can perform high-speed and flexible measurements if binary fringe patterns are defocused by projector properly. However, the actual defocusing degree is difficult to set, and the fringe period is difficult to determine accordingly. In this study, we present a square-binary defocusing parameter selection framework. First, we analyze the fringe formation process mathematically. The defocusing degree is quantified and manipulated by using the focusing distance of projector, which is calibrated by point spread function measurement. To optimize parameter selection, single-point sinusoidal error is modeled as the objective function for the evaluation of the defocusing effect. We verify the correctness by using different parameter combinations and object measurements in our experiments. The appropriate defocusing parameters can be easily obtained according to the analysis of practical system setup, which improves the quality and robustness of the system.

A High Throughput Integrated Hyperspectral Imaging and 3D Measurement System.

Hyperspectral and three-dimensional measurements can obtain the intrinsic physicochemical properties and external geometrical characteristics of objects, respectively. The combination of these two kinds of data can provide new insights into objects, which has gained attention in the fields of agricultural management, plant phenotyping, cultural heritage conservation, and food production. Currently, a variety of sensors are integrated into a system to collect spectral and morphological information in agriculture. However, previous experiments were usually performed with several commercial devices on a single platform. Inadequate registration and synchronization among instruments often resulted in mismatch between spectral and 3D information of the same target. In addition, using slit-based spectrometers and point-based 3D sensors extends the working hours in farms due to the narrow field of view (FOV). Therefore, we propose a high throughput prototype that combines stereo vision and grating dispersion to simultaneously acquire hyperspectral and 3D information. Furthermore, fiber-reformatting imaging spectrometry (FRIS) is adopted to acquire the hyperspectral images. Test experiments are conducted for the verification of the system accuracy, and vegetation measurements are carried out to demonstrate its feasibility. The proposed system is an improvement in multiple data acquisition and has the potential to improve plant phenotyping.

Calibration of AOTF-based 3D measurement system using multiplane model based on phase fringe and BP neural network.

A specifically designed imaging system based on an acousto-optic tunable filter (AOTF) can integrate hyperspectral imaging and 3D reconstruction. As a result of the complicated optical structure, the AOTF imaging system deviates from the traditional pinhole model and lens distortion form, causing difficulty to achieve precise camera calibration. The influencing factors leading to the deviation are discussed and a multiplane model (MPM) is proposed with phase fringe to produce dense mark points and a back propagation neural network to obtain subpixel calibration. Experiments show that MPM can reduce the back projection error efficiently compared with the pinhole model. A 3D reconstruction process is conducted based on the calibration result to verify the feasibility of the proposed method.

High-speed triangular pattern phase-shifting 3D measurement based on the motion blur method.

Recent advancements in 3D measurement technologies have increased the urgency of requiring high-speed 3D measurement in many fields. This study presents a novel four-step triangular pattern phase-shifting 3D measurement using the motion blur method, which combines the advantages of phase-shifting methods. To comply with the high speed requirement, binary coded triangular patterns are projected and could dither vertically. Therefore, the image captured by the camera is blurred into grayscale-intensity triangular patterns, which can be used for phase unwrapping and 3D reconstruction. The proposed method decreased the projection time compared with sinusoidal patterns using a DMD (digital micromirror device) projector. Furthermore, this study presents a four-step triangular phase-shifting unwrapping algorithm. The experiments indicate that the proposed method can achieve high-speed 3D measurement and reconstruction.

Adaptive regional single-pixel imaging based on the Fourier slice theorem.

Single-pixel imaging (SPI) is a novel method for capturing high-quality 2D images of scenes using a non-spatially-resolved detector. While implementing conventional SPI, a huge number of illuminated patterns are projected onto the object to reconstruct a sharp image. For a situation in which the object occupies part of the illuminated region, we propose an adaptive regional SPI method (ARSI) to decrease the number of projected patterns. In the ARSI scheme, the object region is adaptively located based on the Fourier slice theorem. Then, the illuminated patterns are projected only onto the object region to facilitate imaging efficiency. Experiments demonstrate that the proposed ARSI method can achieve sharp image reconstruction with a substantial reduction in pattern number, thereby improving imaging efficiency.

Active-target-based calibration of relative poses of mirrors in intraoral scanners.

This paper describes a practical method using an active target to calibrate relative poses of mirrors in intraoral scanners. Intraoral scanning is a fast-growing technology. Mirrors are widely used in intraoral scanners to increase the measuring area of a single view. The relative poses of these mirrors must be calibrated for accurate three-dimensional profiling. We present and analyze the geometric model of multiview mirrors. A calibration method for relative poses of mirrors is developed based on fringe projection. Vertical and horizontal fringes are displayed on an active target, and every pixel can be viewed as a calibration marker. This calibration method allows the mirrors to have a narrow common field of view. A cell phone display is chosen as the active target, and experimental results demonstrate the effectiveness of the proposed method compared to traditional methods.

Hyper thin 3D edge measurement of honeycomb core structures based on the triangular camera-projector layout & phase-based stereo matching.

We propose a novel hyper thin 3D edge measurement technique to measure the profile of 3D outer envelope of honeycomb core structures. The width of the edges of the honeycomb core is less than 0.1 mm. We introduce a triangular layout design consisting of two cameras and one projector to measure hyper thin 3D edges and eliminate data interference from the walls. A phase-shifting algorithm and the multi-frequency heterodyne phase-unwrapping principle are applied for phase retrievals on edges. A new stereo matching method based on phase mapping and epipolar constraint is presented to solve correspondence searching on the edges and remove false matches resulting in 3D outliers. Experimental results demonstrate the effectiveness of the proposed method for measuring the 3D profile of honeycomb core structures.