Accuracy Of Height Measurements Research Articles

Predictive accuracy of saggital height measurements in optimizing scleral contact lens fitting

Aims/Purpose: To evaluate the accuracy of corneal and scleral tomography analysis for determining the initial selection of a 16.5 mm scleral lens to enhance fitting outcomes and patient comfort.Methods: This single‐site, consecutive study fitted scleral lenses in 30 eyes in 16 patients (mean age 39.7 yrs., 11 males)). Patients underwent comprehensive evaluations, including detailed corneal and scleral tomography. Initial fitting used the manufacturer's standard protocol. Lens fitting was assessed with Anterior Segment OCT after 1 hour of wear, focusing on vaulting and overall fit. The required 300‐micron central sagittal vaulting was compared with tomography measurements at 10 mm, the limbal area, and 15 mm.Results: The group included 24 eyes with keratoconus, 2 with high regular astigmatism, and 4 with dry eyes. The mean HVID was 12.05 mm (SD = 0.33 mm, 95% CI: 11.92‐12.18 mm). The mean central corneal astigmatism was 2.91 D (SD = 1.74 D, 95% CI: 2.22‐3.60 D). Mean sagittal heights were 1869.3 microns (SD = 172.4, 95% CI: 1800.7‐1937.9) at 10 mm, 2727.7 microns (SD = 287.6, 95% CI: 2620.4‐2835.0) at the limbus, and 3970.5 microns (SD = 308.5, 95% CI: 3850.0‐4091.0) at 15 mm. The estimated ideal sagittal depth was 4321.8 microns (SD = 258.6, 95% CI: 4233.6‐4410.0). Sagittal height at 15 mm was the strongest predictor for ideal lens fitting (R2 = 0.9367). The multiple regression model, including all three measurements, showed a marginal improvement in accuracy (R2 = 0.947).Conclusions: The sagittal height at 15 mm is a highly effective predictor for initial scleral lens fittings, providing significant accuracy. This measurement can streamline the fitting process, reduce chair time, improve clinical outcomes, and increase patient comfort.

Plant height measurement using UAV-based aerial RGB and LiDAR images in soybean.

Phenotypic traits like plant height are crucial in assessing plant growth and physiological performance. Manual plant height measurement is labor and time-intensive, low throughput, and error-prone. Hence, aerial phenotyping using aerial imagery-based sensors combined with image processing technique is quickly emerging as a more effective alternative to estimate plant height and other morphophysiological parameters. Studies have demonstrated the effectiveness of both RGB and LiDAR images in estimating plant height in several crops. However, there is limited information on their comparison, especially in soybean (Glycine max [L.] Merr.). As a result, there is not enough information to decide on the appropriate sensor for plant height estimation in soybean. Hence, the study was conducted to identify the most effective sensor for high throughput aerial phenotyping to estimate plant height in soybean. Aerial images were collected in a field experiment at multiple time points during soybean growing season using an Unmanned Aerial Vehicle (UAV or drone) equipped with RGB and LiDAR sensors. Our method established the relationship between manually measured plant height and the height obtained from aerial platforms. We found that the LiDAR sensor had a better performance (R2 = 0.83) than the RGB camera (R2 = 0.53) when compared with ground reference height during pod growth and seed filling stages. However, RGB showed more reliability in estimating plant height at physiological maturity when the LiDAR could not capture an accurate plant height measurement. The results from this study contribute to identifying ideal aerial phenotyping sensors to estimate plant height in soybean during different growth stages.

Adherence to Lung Protective Ventilation in ARDS: A Mixed Methods Study Using Real-Time Continuously Monitored Ventilation Data.

Background: Lung-protective ventilation is a standard intervention for mitigating ventilator-induced lung injury in patients with ARDS. Despite its efficacy, adherence to contemporary evidence-based guidelines remains suboptimal. We aimed to identify factors that affect the adherence of staff to applying lung-protective ventilation guidelines by analyzing real-time, continuously monitored ventilation data over a 5-year longitudinal period. Methods: We conducted retrospective cohort and qualitative studies. Subjects with billing code J80 who survived at least 48 h of continuous mandatory ventilation with volume control in critical care settings between January 1, 2018, and December 31, 2022, were eligible. Tidal volume was measured dynamically (1-min resolution) and averaged hourly. The lung-protective ventilation setting studied was ≤6 mL/kg predicted body weight. A subgroup analysis was conducted by considering COVID-19 status. Focus groups of critical-care providers were convened to investigate the possible reasons for the non-utilization of lung-protective ventilation. Results: Among 1,055 subjects, 42.4% were on lung-protective ventilation settings at 48 h. Male sex was correlated with lung-protective ventilation (odds ratio [OR] 1.63, 95% CI 1.08-2.47), whereas age ≥60 y was associated with no lung-protective ventilation use (OR 0.61, 95% CI 0.39-0.94] in the subjects with non-COVID-19 etiologies. Improved staff adherence was observed in the subjects with COVID-19 early in the pandemic when COVID-19 (OR 1.48, 95% CI 1.07-2.04), male sex (OR 2.42, 95% CI 1.79-3.29), and neuromuscular blocking agent use within 48 h (OR 1.69, 95% CI 1.25-2.29) were correlated with staff placing subjects on lung-protective ventilation. However, lung-protective ventilation use occurred less frequently by staff managing subjects with cancer (OR 0.59, 95% CI 0.35-0.99) and hypertension (OR 0.62, 95% CI 0.45-0.85). Focus groups supported these findings and highlighted the need for an accurate height measurement on unit admission to determine the appropriate target tidal volume. Conclusions: Staff are not yet universally adherent to lung-protective ventilation best practices. Strategies, for example, continuous monitoring, with frequent feedback to clinical teams may help.

Performance assessment of interpolation methods for orbits of altimetry satellites

Global and regional sea level variations are important indicators of climate change and are derived from accurate sea surface height measurements and precisely determined orbits of altimetry satellites. To validate and improve the quality of these orbits, comparisons with external solutions are important. Since orbit solutions of different institutions are not necessarily provided at the same time instants, interpolation is required for comparison. In this study, we investigate the appropriate interpolation method and its degree to reduce interpolation errors to sub-millimetre levels. We also assess the magnitude of errors occurring at transformations when expressing orbit differences not only in the terrestrial reference frame (Cartesian coordinates), but also in local orbital and ellipsoidal coordinates. The analyses conducted in this study provide good results for Hermite interpolation of degrees 7–11 and Newton interpolation of at least degree 9 with a three-dimensional interpolation error of 0.6 mm and a scattering of 0.2 mm on average for satellite coordinates given with an accuracy of 1 mm in the SP3 format. These interpolation settings limit transformation errors between coordinate systems to ±0.01 mm and incorrect mapping of interpolation errors into certain components in the target system to ±0.02 mm. The spectral analysis of orbit differences is affected up to 0.1 mm in magnitude with appropriate interpolation settings. Extending the number of decimal digits of the satellite position and velocity in SP3 files by one digit benefits the orbit comparisons and reduces the interpolation error by 90% from 0.6 to 0.06 mm. The results are obtained using piece-wise interpolation and a validity interval inside the interpolation interval to minimise the effects of the Runge phenomenon.Graphical

Height Measurement for Meter-Wave MIMO Radar Based on Sparse Array Under Multipath Interference

For meter-wave multiple-input multiple-output (MIMO) radar, the multipath of target echoes may cause severe errors in height measurement, especially in the case of complex terrain where terrain fluctuation, ground inclination, and multiple reflection points exist. Inspired by a sparse array with greater degrees of freedom and low mutual coupling, a height measurement method based on a sparse array is proposed. First, a practical signal model of MIMO radar based on a sparse array is established. Then, the modified multiple signal classification (MUSIC) and maximum likelihood (ML) estimation algorithms based on two classical sparse arrays (coprime array and nested array) are proposed. To reduce the complexity of the algorithm, a real-valued processing algorithm for generalized MUSIC (GMUSIC) and maximum likelihood is proposed, and a reduced dimension matrix is introduced into the real-valued processing algorithm to further reduce computation complexity. Finally, sufficient simulation results are provided to illustrate the effectiveness and superiority of the proposed technique. The simulation results show that the height measurement accuracy can be efficiently improved by using our proposed technique for both simple and complex terrain.

Adherence to Lung Protective Ventilation in ARDS: A Mixed Methods Study Using Real-Time Continuously Monitored Ventilation Data.

Lung-protective ventilation is a standard intervention for mitigating ventilator-induced lung injury in patients with ARDS. Despite its efficacy, adherence to contemporary evidence-based guidelines remains suboptimal. We aimed to identify factors that affect the adherence of staff to applying lung-protective ventilation guidelines by analyzing real-time, continuously monitored ventilation data over a 5-year longitudinal period. We conducted retrospective cohort and qualitative studies. Subjects with billing code J80 who survived at least 48 h of continuous mandatory ventilation with volume control in critical care settings between January 1, 2018, and December 31, 2022, were eligible. Tidal volume was measured dynamically (1-min resolution) and averaged hourly. The lung-protective ventilation setting studied was ≤ 6 mL/kg predicted body weight. A subgroup analysis was conducted by considering COVID-19 status. Focus groups of critical-care providers were convened to investigate the possible reasons for the non-utilization of lung-protective ventilation. Among 1,055 subjects, 42.4% were on lung-protective ventilation settings at 48 h. Male sex was correlated with lung-protective ventilation (odds ratio [OR] 1.63, 95% CI 1.08-2.47), whereas age ≥ 60 y was associated with no lung-protective ventilation use (OR 0.61, 95% CI 0.39-0.94] in the subjects with non-COVID-19 etiologies. Improved staff adherence was observed in the subjects with COVID-19 early in the pandemic when COVID-19 (OR 1.48, 95% CI 1.07-2.04), male sex (OR 2.42, 95% CI 1.79-3.29), and neuromuscular blocking agent use within 48 h (OR 1.69, 95% CI 1.25-2.29) were correlated with staff placing subjects on lung-protective ventilation. However, lung-protective ventilation use occurred less frequently by staff managing subjects with cancer (OR 0.59, 95% CI 0.35-0.99) and hypertension (OR 0.62, 95% CI 0.45-0.85). Focus groups supported these findings and highlighted the need for an accurate height measurement on unit admission to determine the appropriate target tidal volume. Staff are not yet universally adherent to lung-protective ventilation best practices. Strategies, for example, continuous monitoring, with frequent feedback to clinical teams may help.

Training to improve the capacity of posyandu toddler cadres in early detection of stunting

Early detection of stunting is crucial to optimize the role of posyandu cadres in comprehensive stunting prevention, including anthropometric measurements, result interpretation, documentation, and education for parents. The problem in Randusari Village is the low level of knowledge among cadres regarding early detection of stunting, especially related to accurate height measurement and providing education on fulfilling toddler nutrition. This community service aimed to improve the capacity of posyandu cadres in Randusari Village through structured training. The methods used in this activity were lectures, discussions, role-playing, and evaluation. The results of the training showed a significant increase in cadres' understanding of early detection of stunting and IEC skills. This training successfully improved the cadres' ability to participate in stunting prevention and reduction efforts in Randusari Village. Furthermore, the cadres were facilitated with educational media in the form of food models and “Cegah Stunting” booklets to facilitate the dissemination of the stunting reduction acceleration program in Boyolali Regency.

A Non-Contacted Height Measurement Method in Two-Dimensional Space.

Height is an important health parameter employed across domains, including healthcare, aesthetics, and athletics. Numerous non-contact methods for height measurement exist; however, most are limited to assessing height in an upright posture. This study presents a non-contact approach for measuring human height in 2D space across different postures. The proposed method utilizes computer vision techniques, specifically the MediaPipe library and the YOLOv8 model, to analyze images captured with a smartphone camera. The MediaPipe library identifies and marks joint points on the human body, while the YOLOv8 model facilitates the localization of these points. To determine the actual height of an individual, a multivariate linear regression model was trained using the ratios of distances between the identified joint points. Data from 166 subjects across four distinct postures: standing upright, rotated 45 degrees, rotated 90 degrees, and kneeling were used to train and validate the model. Results indicate that the proposed method yields height measurements with a minimal error margin of approximately 1.2%. Future research will extend this approach to accommodate additional positions, such as lying down, cross-legged, and bent-legged. Furthermore, the method will be improved to account for various distances and angles of capture, thereby enhancing the flexibility and accuracy of height measurement in diverse contexts.

Accuracy of Bone Height and Thickness Measurements in Cone Beam Computed Tomography in the Presence of Porcelain Fused to Metal (PFM) Crowns

Accuracy of Bone Height and Thickness Measurements in Cone Beam Computed Tomography in the Presence of Porcelain Fused to Metal (PFM) Crowns

Unoccupied-Aerial-Systems-Based Biophysical Analysis of Montmorency Cherry Orchards: A Comparative Study

With the global population on the rise and arable land diminishing, the need for sustainable and precision agriculture has become increasingly important. This study explores the application of unoccupied aerial systems (UAS) in precision agriculture, specifically focusing on Montmorency cherry orchards in Payson, Utah. Despite the widespread use of UAS for various crops, there is a notable gap in research concerning cherry orchards, which present unique challenges due to their physical structure. UAS data were gathered using an RTK-enabled DJI Mavic 3M, equipped with both RGB and multispectral cameras, to capture high-resolution imagery. This research investigates two primary applications of UAS in cherry orchards: tree height mapping and crop health assessment. We also evaluate the accuracy of tree height measurements derived from three UAS data processing software packages: Pix4D, Drone2Map, and DroneDeploy. Our results indicated that DroneDeploy provided the closest relationship to ground truth data with an R2 of 0.61 and an RMSE of 31.83 cm, while Pix4D showed the lowest accuracy. Furthermore, we examined the efficacy of RGB-based vegetation indices in predicting leaf area index (LAI), a key indicator of crop health, in the absence of more expensive multispectral sensors. Twelve RGB-based indices were tested for their correlation with LAI, with the IKAW index showing the strongest correlation (R = 0.36). However, the overall explanatory power of these indices was limited, with an R2 of 0.135 in the best-fitting model. Despite the promising results for tree height estimation, the correlation between RGB-based indices and LAI was underwhelming, suggesting the need for further research.

Improving GNSS-IR Sea Surface Height Accuracy Based on a New Ionospheric Stratified Elevation Angle Correction Model

Approximately 71% of the Earth’s surface is covered by vast oceans. With the exacerbation of global climate change, high-precision monitoring of sea surface height variations is of vital importance for constructing global ocean gravity fields and preventing natural disasters in the marine system. Global Navigation Satellite System Interferometry Reflectometry (GNSS-IR) sea surface altimetry is a method of inferring sea surface height based on the signal-to-noise ratio of satellite signals. It enables the retrieval of sea surface height variations with high precision. However, navigation satellite signals are influenced by the ionosphere during propagation, leading to deviations in the measured values of satellite elevation angles from their true values, which significantly affects the accuracy of GNSS-IR sea surface altimetry. Based on this, the contents of this paper are as follows: Firstly, a new ionospheric stratified elevation angle correction model (ISEACM) was developed by integrating the International Reference Ionosphere Model (IRI) and ray tracing methods. This model aims to improve the accuracy of GNSS-IR sea surface altimetry by correcting the ionospheric refraction effects on satellite elevation angles. Secondly, four GNSS stations (TAR0, PTLD, GOM1, and TPW2) were selected globally, and the corrected sea surface height values obtained using ISEACM were compared with observed values from tide gauge stations. The calculated average Root Mean Square Error (RMSE) and Pearson Correlation Coefficient (PCC) were 0.20 m and 0.83, respectively, indicating the effectiveness of ISEACM in sea surface height retrieval. Thirdly, a comparative analysis was conducted between sea surface height retrieval before and after correction using ISEACM. The optimal RMSE and PCC values with tide gauge station observations were 0.15 m and 0.90, respectively, representing a 20.00% improvement in RMSE and a 4.00% improvement in correlation coefficient compared to traditional GNSS-IR retrieval heights. These experimental results demonstrate that correction with ISEACM can effectively enhance the precision of GNSS-IR sea surface altimetry, which is crucial for accurate sea surface height measurements.

Dynamic three-dimensional measurement and analysis of rotating polygons

Rotating polygons are geometric patterns formed spontaneously by the free surface of a rotating fluid driven by a rotating disk at the bottom of a partially filled cylindrical container. Most previous studies mainly predict the number of polygon apexes as a function of disk rotation speed and initial fluid depth. We propose to experimentally characterize this three-dimensional instability by means of highly accurate measurements of the free surface height using Fourier transform profilometry. For a given initial height of 26 mm in a cylindrical cavity of radius 140 mm, these measurements enabled us to not only revisit quantitatively the previous analysis in the fully developed regime but also extend the analysis to the spin-up regime (starting from rest). This latter regime has not been explored. In addition, we describe the mixed-mode regime at the boundary between two clearly established polygons. Thanks to precise space-time resolved surface height measurements, we propose a decomposition of each azimuthal mode that provides valuable information on the growth and dynamics of rotating polygons and can, therefore, serve as a basis for future numerical simulations and theoretical models.

谷物联合收获机智能化割台技术研究综述

With the rapid advancement of agricultural mechanization, intelligent header technology has emerged as a pivotal element in optimizing the efficiency and quality of grain combine harvesters. This paper offers a comprehensive analysis of the current state of intelligent header technology, with a particular emphasis on the structure, working principles, contour-following mechanisms, and height control technologies. By integrating cutting-edge sensor technologies, advanced control algorithms, and optimized mechanical designs, intelligent headers can achieve precise control over height and posture, thereby significantly reducing crop losses and enhancing both harvesting efficiency and quality. Despite substantial progress, challenges remain in areas such as response speed, real-time performance, height measurement accuracy, and control algorithm effectiveness. Future research will likely concentrate on improving control system performance, refining component and system designs, and incorporating emerging technologies to better accommodate diverse crops and complex terrains. This paper also provides a critical evaluation of current limitations in intelligent header research and projects future trends, offering valuable theoretical and practical insights for optimizing header structures, minimizing losses, and enhancing intelligent functionalities. The ultimate aim is to drive continuous innovation and advancement in header technology for grain combine harvesters.

Development of a correction coefficient for radiographic evaluation of the alveolar bone crest: a pilot study.

To analyze the differences in cusp height on radiographs, establishing proportional relationships between cusp and alveolar bone crest (ABC) measurements. The goal of this study was to develop a correction coefficient by considering this proportion. Twenty-one artificial teeth, molars and premolars, and bovine ribs were used. Interproximal radiographs were taken with the aid of a positioner. The vertical angles used were: 0°, + 5°, and + 10°, and processed using three spatial resolutions measured in line pairs per mm (lp/mm): 20, 25 and 40. The Perio filter was applied to each image, in addition to the original one. Combinations of angle, resolution, and filter were made. Eighteen images were analyzed by three specialists, resulting in 252 measurements for each evaluator, totaling 756 measurements. The overall variability of the measurements can be explained mainly by the variation in tooth anatomy. The 0° 25 lp/mm Perio filter method was the closest one to the actual clinical scenario for both cusps and ABC. The correction factor managed to explain 71.45% of the errors. The variation in vertical angulation interferes with cusp and ABC measurements, and the angulation at 0º and spatial resolution of 25 lp/mm showed better results. The use of correction coefficients allowed approaching actual measurement values. More accurate ABC height measurements are essential even in radiographic exams that do not meet the standard of excellence because the need to repeat radiographic exams is then eliminated.

Enhancing Crop Harvesting with Ultrasonic Stubble Height Sensing Technology

Crop stubble refers to the residual plant material, primarily stems and leaves, that remains in the field after the harvest of the primary crop. In modern farming practices, considering the customer requirement, knowing the crop stubble height is a critical variable in agricultural management to plan for uniform crop cuts by adjusting the header’s cutter height of the harvester. The potential outcome of this research includes an accurate and non-contact stubble height measurement system utilizing ultrasonic sensing technology. The study involves the design and development of an algorithm to calculate short-range and long-range distances using ultrasonic sensors by processing the raw ultrasonic reflections. The proposed algorithm has different signal processing options to convert the raw ultrasonic signal to the distance. These distances are then mapped to the distance from the ground, distance from the cut end of the stubble and resulting stubble height. Setup with the sensor mount is created to mimic the actual field environment and the height detection algorithm is evaluated on corn and wheat crop stubbles. Multiple trials are carried out using the static and dynamic setup for different heights of the stubble. For these trials, the calculated stubble height closely matches with the actual stubble height. Keywords: Combine harvester, stubble height sensing, ultrasonic sensing, Non-Contact Sensing, uniform crop cut, Stubble Management, Agricultural Sensors, Harvest Residue Detection.

A Multi-Plant Height Detection Method Based on Ruler-Free Monocular Computer Vision

Plant height is an important parameter of plant phenotype as one indicator of plant growth. In view of the complexity and scale limitation in current measurement systems, a scaleless method is proposed for the automatic measurement of plant height based on monocular computer vision. In this study, four peppers planted side by side were used as the measurement objects. Two color images of the measurement object were obtained by using a monocular camera at different shooting heights. Binary images were obtained as the images were processed by super-green grayscale and the Otsu method. The binarized images were transformed into horizontal one-dimensional data by the statistical number of vertical pixels, and the boundary points of multiple plants in the image were found and segmented into single-plant binarized images by filtering and searching for valleys. The pixel height was extracted from the segmented single plant image and the pixel displacement of the height was calculated, which was substituted into the calculation together with the reference height displacement to obtain the realistic height of the plant and complete the height measurements of multiple plants. Within the range of 2–3 m, under the light condition of 279 lx and 324 lx, this method can realize the rapid detection of multi-plant phenotypic parameters with a high precision and obtain more accurate plant height measurement results. The absolute error of plant height measurement is not more than ±10 mm, and the absolute proportion error is not more than ±4%.

Neutrophil-to-lymphocyte ratio and lymphocyte count as an alternative to body mass index for screening malnutrition in older adults living in the community.

Accurate height and weight measurement can be challenging in older adults and complicates nutritional status assessment. Other parameters like the neutrophil-to-lymphocyte ratio (NLR) and the lymphocyte count (LC) could be an option to these measurements. We aimed to test these variables as subrogates of body mass index (BMI) or calf-circumference (CC) for malnutrition screening in community-dwelling older adults. This is a secondary analysis from the Salud, Bienestar y Envejecimiento (SABE) survey from Ecuador (2009). Includes data on demographics, health-related factors, physical assessments, and complete blood count, allowing to calculate NLR and LC to be used as part of the Mini Nutritional Assessment (MNA), instead of the BMI. Consequently, 4 models were included: standard MNA, MNA-CC, MNA-NLR and MNA-LC. Finally, age, sex, and comorbidities were considered as confounding variables. In our analysis of 1,663 subjects, 50.81% were women. Positive correlations with standard MNA were found for MNA-NLR (Estimate = 0.654, p < 0.001) MNA-CC (Estimate = 0.875, p value <0.001) and MNA-LC (Estimate = 0.679, p < 0.001). Bland-Altman plots showed the smallest bias in MNA-CC. Linear association models revealed varying associations between MNA variants and different parameters, being MNA-NLR strongly associated with all of them (e.g. Estimate = 0.014, p = 0.001 for albumin), except BMI. The newly proposed model classified a greater number of subjects at risk of malnutrition and fewer with normal nutrition compared to the standard MNA. Additionally, it demonstrated a strong correlation and concordance with the standard MNA. This suggests that hematological parameters may offer an accurate alternative and important insights into malnutrition.

2018–2022年青海省主要湖泊蓄水量时空变化数据集

Qinghai Province is an important ecological function area, which is located in the inland of Northwest China. Qinghai Province is abundant in the total amount of water resource, but the spatial-temporal distribution of water resource in Qinghai Province is extremely uneven. Moreover, due to the factors such as climate and geographical environment, most lakes lack monitoring for a long time. As a significant carrier of surface water resource, lakes are important indicators for studying the impact of climate change and human activities on the water cycle process. The domestic GF-1 and GF-6 satellites have the ability to observe the earth repeatedly for a period of 2 days by collaborating, thus the surface water area can be obtained at high frequency. A high-precision surface water level can be acquired by ICESat-2, which has centimeter-level height measurement accuracy. The water area derived from GF-1/6 and water level derived from ICESat-2 were adopted to build the models for monitoring spatial-temporal variation of water storage of lakes in Qinghai Province. We developed a dataset of spatial-temporal variation of lake water storage in Qinghai Province during 2018–2022 via the models. The monitoring accuracy of the dataset had been verified with an overall accuracy better than 93%, which meets the needs of remote sensing monitoring of spatial-temporal variation of lake water storage. The dataset contains a total of 60 monthly storage variation of 33 lakes an area of more than 30 km2 in Qinghai Province during 2018–2022. These lakes are mainly distributed in the west, north and southeast of Qinghai Province. The dataset can provide basic data support for lake, hydrological and climate change process monitoring, dynamic evaluation of water resources, and optimization of water resources management and scheduling in Qinghai Province.

Comparative analysis of digital holographic microscopy and digital lensless holographic microscopy for quantitative phase imaging

This study provides a detailed comparison of two widely used quantitative phase imaging (QPI) techniques: single-shot off-axis digital holographic microscopy (DHM) and digital lensless holographic microscopy (DLHM). The primary aim is to evaluate and contrast critical aspects of their imaging performance, including spatial phase sensitivity, phase measurement accuracy, and spatial lateral resolution. Employing typical configurations for both DHM and DLHM, the study utilizes a customized phase test target featuring linear phase changes introduced by a specially designed linear density attenuation filter. Ground truth data from an atomic force microscope is incorporated to validate the experimental findings. The comparative analysis reveals that DHM and DLHM exhibit nearly identical spatial phase sensitivity, with DHM demonstrating a minimal 3.2% measurement error compared to DLHM's 4% in height measurement accuracy. Notably, DHM achieves a finer spatial lateral resolution down to 3.1 µm, surpassing DLHM's 5.52 µm. While DHM outperforms DLHM in precision and resolution, the latter offers advantages in terms of portability and cost-effectiveness. These findings provide valuable insights for researchers and practitioners, aiding in the informed selection of QPI methods based on specific application requirements.

A solution to the problem of height overcompensation in GNSS-IR corn height measurements: a canopy reflectance calibration model

ABSTRACT The global navigation satellite system interferometric reflectometry (GNSS-IR) technique for collecting corn height has the limitation of not accounting for changes in the corn canopy reflector. A model that uses the corn canopy reflection coefficient to account for changes in the canopy’s reflector and the power attenuation of the signal reflected by the soil surface is proposed. This letter proposes a method to solve the overcompensation problem of traditional GNSS-IR vegetation height measurement. Considering the decrease in GNSS signal penetration depth and the upward shift of the actual reflecting surface caused by changes in corn leaf water content (LWC), this letter provides a calibration model for the GNSS-IR corn height measurement. The GNSS signals reflected from the corn canopy were separated using empirical mode decomposition (EMD), and the height measurement was then calibrated using the directed and reflected signal ratios. The results of the experiments show that the model proposed in this letter can effectively improve the accuracy of corn height measurement, and the root mean square error (RMSE) is reduced to 0.17 m . Compared with the current study, the model proposed in this study reduces the influence of the actual reflective surface variation of the corn canopy on the height measurement using GNSS-IR.