Effect Of Scan Angle Research Articles

Correction of UAV LiDAR-derived grassland canopy height based on scan angle.

Grassland canopy height is a crucial trait for indicating functional diversity or monitoring species diversity. Compared with traditional field sampling, light detection and ranging (LiDAR) provides new technology for mapping the regional grassland canopy height in a time-saving and cost-effective way. However, the grassland canopy height based on unmanned aerial vehicle (UAV) LiDAR is usually underestimated with height information loss due to the complex structure of grassland and the relatively small size of individual plants. We developed canopy height correction methods based on scan angle to improve the accuracy of height estimation by compensating the loss of grassland height. Our method established the relationships between scan angle and two height loss indicators (height loss and height loss ratio) using the ground-measured canopy height of sample plots with 1×1m and LiDAR-derived heigh. We found that the height loss ratio considering the plant own height had a better performance (R2 = 0.71). We further compared the relationships between scan angle and height loss ratio according to holistic (25-65cm) and segmented (25-40cm, 40-50cm and 50-65cm) height ranges, and applied to correct the estimated grassland canopy height, respectively. Our results showed that the accuracy of grassland height estimation based on UAV LiDAR was significantly improved with R2 from 0.23 to 0.68 for holistic correction and from 0.23 to 0.82 for segmented correction. We highlight the importance of considering the effects of scan angle in LiDAR data preprocessing for estimating grassland canopy height with high accuracy, which also help for monitoring height-related grassland structural and functional parameters by remote sensing.

An investigation into lidar scan angle impacts on stand attribute predictions in different forest environments

As studies have underlined the sensitivity of lidar metrics to scan angles, the objective of this study was twofold. Firstly, we further investigated the influence of lidar scan angle on the ABA predictions of stand attributes of riparian (29 field plots), broadleaf (42 field plots), coniferous (31 field plots) and mixed (45 field plots) forest types in France. Secondly, we evaluated the potential of voxelisation approaches to normalise scan angle effects in lidar metrics and mitigate scan angle effects in ABA models. To achieve these objectives, we first selected a model based on four lidar metrics with different sensitivities to lidar scan angle, i.e. mean and variance of canopy height values, gap-fraction, and coefficient of variation of plant area density (PAD) profile. For each plot, we considered the point cloud scanned from one flight line independently and characterised each resulting point cloud by the mean scan angle (MSA) and classified them into one of three classes: A (0° <=MSA < 10°), B (10°<=MSA < 20°) or C (20°<=MSA < 30°). An experimental setup involving nine scenarios was conceived to study the impact of the number of flight lines (scenarios fl1, fl2 and fl3) and predominant scan angle (scenarios A, B or C) or combination of scan angle directions (scenarios A and B, or A and C, or B and C), on area-based approach (ABA) models. We built ABA models for the same forest plots for 5000 resampled datasets in each scenario to predict three forest attributes, i.e., stem and total volume (Vst and Vtot) and basal area (BA). Three goodness-of-fit criteria were computed for each model (coefficient of determination (R2), relative root mean square error (rRMSE) and mean percentage error (MPE). We compared the distributions of the goodness-of-fit criteria between scenarios to assess the behaviour of the predictive models when: 1) the number of flight lines (i.e., scan angles) increases (fl1, fl2 or fl3); 2) lidar datasets comprise specific scan angle (A, B or C) or combination of scan angles (AB, AC or BC); 3) voxelisation is used to compute Pf and CVPAD. The results show that models built with point clouds scanned from multiple flight lines were more robust, with a lower standard deviation of their goodness-of-fit criteria. On average, across all forest types, compared to fl1, the standard deviations of R2 distributions were lower for fl2 and fl3 by 42 % and 77 %, respectively. We also observed that a dataset with a predominantly nadir configuration (i.e., scenario A) did not always result in better predictions (mean R2 higher by 0.08, 0.07, 0.04 for scenario B for broadleaf, coniferous and mixed, respectively). For a set ofcalibration plots, the resulting forest attribute models depend on the acquisition geometry over the plots, as observed in this study, which could result in unreliable wall-to-wall predictions. The risk is particularly high in acquisitions with low overlapping rates, with many areas covered by only one flight line. Using voxel-based Pf and CVPAD together with the mean and variance of heights helped to mitigate the impacts of changes in scan angles by a) increasing the means of the distributions, thereby improving the accuracy of predictions, or b) reducing the standard deviations, thereby increasing prediction precision, or c) both of the above.

Effect of Scanning Angle on Grain Growth and Mechanical Properties of Ni10cr6w1fe9ti1 Hea

Effect of Scanning Angle on Grain Growth and Mechanical Properties of Ni10cr6w1fe9ti1 Hea

Effect of scan angle on ALS metrics and area-based predictions of forest attributes for balsam fir dominated stands

Abstract In this study, we assessed the effect of airborne laser scanning (ALS) scan angle on point cloud metrics and the estimation of forest attributes in balsam fir (Abies balsamea (L.) Mill.) dominated forests of western Newfoundland, Canada. We collected calibration data from ground plot locations representing varying scan angles from two flight lines: within 4° of nadir in one flight line, and either 11–20° from nadir (low scan angle plots: L), or 21–30° from nadir (high scan angle plots: H) in an adjacent flight line. We computed three sets of ALS point cloud metrics for each ground plot using ALS data from: individual flight lines (near-nadir and off-nadir) and data from all available flight lines (up to 4) combined (aggregated, as commonly used in an operational inventory context). We generated three sets of models for each of the L and H plots using the ALS metric sets, and applied the models to independent validation data. We analysed the effect of scan angle on both the ALS metrics and performance statistics for area-based models generated using the L and H datasets. Our results demonstrate that off-nadir scan angles significantly affected (P &amp;lt; 0.05) specific metrics from both L (i.e. coefficient of variation (COVAR)) and H (i.e. maximum height, 95th percentile of height, mean height) plots, although the effects were trivial (mean absolute differences were ≤ 0.01 for COVAR and &amp;lt; 0.3 m for the height metrics). Forest attribute predictions using these and other metrics were also significantly affected (P &amp;lt; 0.05), namely gross merchantable volume (GMV), total volume (TVOL) and aboveground tree biomass (AGB) from L; and Lorey’s mean height (HGT), mean diameter at breast height (DBH), and GMV from H. We further demonstrated that combining ALS data from all available flight lines significantly increased errors for the predictions of HGT, GMV, and TVOL using L, and significantly reduced errors of HGT using H when compared to errors resulting from models developed with near-nadir data. While the differences in prediction errors were significant, they were small, with differences in mean absolute prediction errors all &amp;lt;1.3 per cent. Based on our results, we concluded that the effects of large scan angles, up to 30° off-nadir, on area-based forest attribute predictions were minimal in this study, which used ALS metrics calculated from ALS returns with a height above ground &amp;gt;2 m for balsam fir-dominated forests. This result may provide for operational efficiencies in implementing enhanced forest inventories in this particular forest environment.

Improving the Consistency of Nanoscale Etching for Atomic Force Microscopy Tomography Applications

The atomic force microscope empowers research into nanoscale structural and functional material properties. Recently, the scope of application has broadened with the arrival of conductance tomography, a technique for mapping current in three-dimensions in electronic devices by gradually removing sample material with the scanning probe. This technique has been valuable in studying resistance switching memories and solar cells, although its broader use has been hindered by a lack of understanding of its reliability and practicality. Implementation can be preclusive, owing to difficulties in characterizing tip-sample interactions and accounting for probe degradation, both of which are crucial factors in process efficacy. This work follows the existing conductance tomography literature, presenting an insight into the repeatability and reliability of the material removal processes. The consistency of processes on a hard oxide and a softer metal are investigated, to understand the critical differences in etching behavior that might affect tomography measurements on heterostructures. Individual probe behavior stabilizes following a wearing-in stage and etching processes are consistent between probes, in particular on oxide. However, process inconsistency increases with applied force on metal. The effects of scan angle, tip speed and feedback gain are therefore explored and their tuning found to improve the spatial consistency of material removal. With these findings, we aim to present a critical study of the implementation of tomography with the atomic force microscope in order to contribute to its methodological development.

Exploring the stability and residual response versus scan angle effects in SNPP VIIRS sensor data record reflectance products using deep convective clouds

The reflective solar bands (RSB) of the Visible and Infrared Imaging Radiometer Suite (VIIRS) on Suomi National Polar-orbiting Partnership satellite are calibrated using solar diffuser and lunar observations. To evaluate the performance of the VIIRS RSB calibration, the deep convective clouds (DCC) are utilized as invariant targets to assess the stability of NASA’s VIIRS sensor data record (SDR) reflectance product for 10 moderate resolution bands (M-bands, M1 to M5 and M7 to M11) and three imagery resolution bands (I-bands, I1 to I3). All the frames along with each scan are divided into six aggregation zones for the scan angle. An empirical bidirectional reflectance distribution function (BRDF) correction is performed to SDR reflectances over DCC to reduce the scattering anisotropy in view and solar angles. The BRDF-corrected reflectances are used to assess the stability and to explore the residual RVS effects for selected bands. Results of this study show that after more than 6 years of on-orbit operation, the use of the prelaunch-based RVS still meets the radiometric requirement for the VIIRS RSB. Examination of the small but noticeable RVS residuals indicates they occur in a few shortest wavelength bands based on a time-dependent quadratic fit of the reflectance trends obtained at all scan angle zones. As the mission continues, continuing monitoring of on-orbit RVS stability and its effects on VIIRS SDR reflectance products are necessary with the DCC technique in the future VIIRS calibrations to ensure the quality of the RSB SDR products.

A Novel method to generate on-board 4D MRI using prior 4D MRI and on-board kV projections from a conventional LINAC for target localization in liver SBRT.

On-board MRI can provide superb soft tissue contrast for improving liver SBRT localization. However, the availability of on-board MRI in clinics is extremely limited. On the contrary, on-board kV imaging systems are widely available on radiotherapy machines, but its capability to localize tumors in soft tissue is limited due to its poor soft tissue contrast. This study aims to explore the feasibility of using an on-board kV imaging system and patient prior knowledge to generate on-board four-dimensional (4D)-MRI for target localization in liver SBRT. Prior 4D MRI volumes were separated into end of expiration (EOE) phase (MRIprior ) and all other phases. MRIprior was used to generate a synthetic CT at EOE phase (sCTprior ). On-board 4D MRI at each respiratory phase was considered a deformation of MRIprior . The deformation field map (DFM) was estimated by matching DRRs of the deformed sCTprior to on-board kV projections using a motion modeling and free-form deformation optimization algorithm. The on-board 4D MRI method was evaluated using both XCAT simulation and real patient data. The accuracy of the estimated on-board 4D MRI was quantitatively evaluated using Volume Percent Difference (VPD), Volume Dice Coefficient (VDC), and Center of Mass Shift (COMS). Effects of scan angle and number of projections were also evaluated. In the XCAT study, VPD/VDC/COMS among all XCAT scenarios were 10.16±1.31%/0.95±0.01/0.88±0.15mm using orthogonal-view 30° scan angles with 102 projections. The on-board 4D MRI method was robust against the various scan angles and projection numbers evaluated. In the patient study, estimated on-board 4D MRI was generated successfully when compared to the "reference on-board 4D MRI" for the liver patient case. A method was developed to generate on-board 4D MRI using prior 4D MRI and on-board limited kV projections. Preliminary results demonstrated the potential for MRI-based image guidance for liver SBRT using only a kV imaging system on a conventional LINAC.

A mathematical framework to describe the effect of beam incidence angle on metrics derived from airborne LiDAR: The case of forest canopies approaching turbid medium behaviour

Airborne laser scanning (LiDAR) is used in forest inventories to quantify stand structure with three-dimensional point clouds. However, the 3D distribution of the point clouds depends not only on stand structure, but also on scan angle, because the probability for an oblique beam to be reflected by the canopy increases with the distance it must travel through the canopy. Thus, the canopy appears to increase in density as the incidence angle increases, all else being equal. The resulting variation between and within datasets can induce bias in LiDAR metrics derived from the vertical distribution of points. In this study, we modelled the effect of scan angle on the vertical structure of the point clouds to predict the bias of metrics derived from points sampled off-nadir. Comparison with paired observations from different flightlines (off- and at-nadir observations of the same point) demonstrated that the model accurately reproduced the bias of metrics calculated for a northern hardwood forest with relatively continuous canopy. Thus, the model could be used to correct the bias of LiDAR metrics, and provides a mathematical framework that could be used to inform the selection of maximum incidence angle in LiDAR surveys, considering the trade-off between decreasing acquisition costs and obtaining unbiased measurements.

Retrieving Directional Gap Fraction, Extinction Coefficient, and Effective Leaf Area Index by Incorporating Scan Angle Information From Discrete Aerial Lidar Data

The scan angle information implicitly contained within the 3-D point cloud data (PCD) generated from light detection and ranging strongly affects the retrieval accuracy of the forest canopy structural parameters. Using information generated from overlapping aerial laser scanning (ALS) flight paths with multiple scan angles over a forest canopy can help to remove the occlusion effects between foliage elements, ultimately creating a relative comprehensive PCD. In this paper, we develop a novel physically based scan angle correction algorithm to retrieve the effective leaf area index (LAIe) of a forest canopy using ALS. Furthermore, we investigate the effects of scan angle and the number of ALS overpass lines from adjacent flight paths over a forest canopy on directional gap fraction (DGF) estimates. Our results suggest that ALS-based LAIe estimates capture 71.35% of the variations in LAIe derived from digital hemispherical photography. A forest canopy point cloud created using PCD from multiple overlapping ALS flight paths was sufficient to quantitatively reveal the anisotropy characteristics of DGF variations. These results suggest that scan angle information should not be neglected in retrieving forest canopy structural parameters, especially when using ALS data collected with a wide scan angle (i.e., −30° to 30° in this paper). Finally, this paper provides a solid foundation to characterize the 3-D spatial distribution of a forest radiation regime using ALS-based forest PCD.

Tree species classification in subtropical forests using small-footprint full-waveform LiDAR data

The accurate classification of tree species is critical for the management of forest ecosystems, particularly subtropical forests, which are highly diverse and complex ecosystems. While airborne Light Detection and Ranging (LiDAR) technology offers significant potential to estimate forest structural attributes, the capacity of this new tool to classify species is less well known. In this research, full-waveform metrics were extracted by a voxel-based composite waveform approach and examined with a Random Forests classifier to discriminate six subtropical tree species (i.e., Masson pine (Pinus massoniana Lamb.)), Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), Slash pines (Pinus elliottii Engelm.), Sawtooth oak (Quercus acutissima Carruth.) and Chinese holly (Ilex chinensis Sims.) at three levels of discrimination. As part of the analysis, the optimal voxel size for modelling the composite waveforms was investigated, the most important predictor metrics for species classification assessed and the effect of scan angle on species discrimination examined. Results demonstrate that all tree species were classified with relatively high accuracy (68.6% for six classes, 75.8% for four main species and 86.2% for conifers and broadleaved trees). Full-waveform metrics (based on height of median energy, waveform distance and number of waveform peaks) demonstrated high classification importance and were stable among various voxel sizes. The results also suggest that the voxel based approach can alleviate some of the issues associated with large scan angles. In summary, the results indicate that full-waveform LIDAR data have significant potential for tree species classification in the subtropical forests.

Aplicación del Láser Escáner Terrestre (TLS) a la modelización de estructuras: precisión, exactitud y diseño de la adquisición de datos en casos reales

Terrestrial laser scanner is employed in a wide range of engineering applications, because of the specifications of TLS units and the good precision reached. This paper presents the application of TLS to structures and walls modeling. It analyzes the factors that influence final accuracy: cloud registration, target type and the effect of scanning angle and distance. A field test was performed with calibrated panels, obtaining real precision and accuracy values for the most common distance ranges in engineering. We propose and validate the usage of pattern graphs relating precision and accuracy versus distance and scanning angle for field survey design. The application of pattern graph in the design of field scan surveys for dam movement control is also presented. Recommendations are made for the application of TLS technique to large structures.

A comparison of waveform processing algorithms for single-wavelength LiDAR bathymetry

Due to the low-cost and lightweight units, single-wavelength LiDAR bathymetric systems are an ideal option for shallow-water (<12m) bathymetry. However, one disadvantage of such systems is the lack of near-infrared and Raman channels, which results in difficulties in extracting the water surface. Therefore, the choice of a suitable waveform processing method is extremely important to guarantee the accuracy of the bathymetric retrieval. In this paper, we test six algorithms for single-wavelength bathymetric waveform processing, i.e. peak detection (PD), the average square difference function (ASDF), Gaussian decomposition (GD), quadrilateral fitting (QF), Richardson–Lucy deconvolution (RLD), and Wiener filter deconvolution (WD). To date, most of these algorithms have previously only been applied in topographic LiDAR waveforms captured over land. A simulated dataset and an Optech Aquarius dataset were used to assess the algorithms, with the focus being on their capability of extracting the depth and the bottom response. The influences of a number of water and equipment parameters were also investigated by the use of a Monte Carlo method. The results showed that the RLD method had a superior performance in terms of a high detection rate and low errors in the retrieved depth and magnitude. The attenuation coefficient, noise level, water depth, and bottom reflectance had significant influences on the measurement error of the retrieved depth, while the effects of scan angle and water surface roughness were not so obvious.

Mirror contamination in space I: mirror modelling

Abstract. We present a comprehensive model that can be employed to describe and correct for degradation of (scan) mirrors and diffusers in satellite instruments that suffer from changing optical Ultraviolet to visible (UV–VIS) properties during their operational lifetime. As trend studies become more important, so does the importance of understanding and correcting for this degradation. This is the case not only with respect to the transmission of the optical components, but also with respect to wavelength, polarisation, or scan-angle effects. Our hypothesis is that mirrors in flight suffer from the deposition of a thin absorbing layer of contaminant, which slowly builds up over time. We describe this with the Mueller matrix formalism and Fresnel equations for thin multi-layer contamination films. Special care is taken to avoid the confusion often present in earlier publications concerning the Mueller matrix calculus with out-of-plane reflections. The method can be applied to any UV–VIS satellite instrument. We illustrate and verify our approach to the optical behaviour of the multiple scan mirrors of SCIAMACHY (onboard ENVISAT).

Effect of scanning angle on vegetation metrics derived from a nationwide Airborne Laser Scanning acquisition

The influence of scanning angle on vegetation metrics derived from a large area Airborne Laser Scanning (ALS) data acquisition was evaluated in this study. The ALS data were derived from the ongoing acquisition for the new Swedish Nationwide Elevation Model. To make a comparison of scanning angles, a random selection of 2310 sample plots (0.01 ha in size) was taken from two large forested areas in the north and south of Sweden. Only plots that had ALS data from two different acquisitions on the same day were used: the first scanned at nadir (0° scanning angle) and the second with an absolute scanning angle ranging from 0° to a nominal 20°. For each plot, 32 plot-level vegetation metrics were calculated from the ALS data for each pair of scanning angles. The ALS metrics for each pair were then compared using a nonparametric Wilcoxon signed-rank test. The results indicated that most metrics commonly used in area-based prediction of forest variables were relatively unaffected by high scanning angles, up to 20°. However, the vegetation ratio and the understory ratio from scanning angles greater than 10° were significantly different from those derived from a 0° scanning angle.

A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data

Digital breast tomosynthesis (DBT) is a promising breast cancer screening tool that has already begun making inroads into clinical practice. However, there is ongoing debate over how to quantitatively evaluate and optimize these systems, because different definitions of image quality can lead to different optimal design strategies. Powerful and accurate tools are desired to extend our understanding of DBT system optimization and validate published design principles. The authors developed a virtual trial framework for task-specific DBT assessment that uses digital phantoms, open-source x-ray transport codes, and a projection-space, spatial-domain observer model for quantitative system evaluation. The authors considered evaluation of reconstruction algorithms as a separate problem and focused on the information content in the raw, unfiltered projection images. Specifically, the authors investigated the effects of scan angle and number of angular projections on detectability of a small (3 mm diameter) signal embedded in randomly-varying anatomical backgrounds. Detectability was measured by the area under the receiver-operating characteristic curve (AUC). Experiments were repeated for three test cases where the detectability-limiting factor was anatomical variability, quantum noise, or electronic noise. The authors also juxtaposed the virtual trial framework with other published studies to illustrate its advantages and disadvantages. The large number of variables in a virtual DBT study make it difficult to directly compare different authors' results, so each result must be interpreted within the context of the specific virtual trial framework. The following results apply to 25% density phantoms with 5.15 cm compressed thickness and 500 μm(3) voxels (larger 500 μm(2) detector pixels were used to avoid voxel-edge artifacts): 1. For raw, unfiltered projection images in the anatomical-variability-limited regime, AUC appeared to remain constant or increase slightly with scan angle. 2. In the same regime, when the authors fixed the scan angle, AUC increased asymptotically with the number of projections. The threshold number of projections for asymptotic AUC performance depended on the scan angle. In the quantum- and electronic-noise dominant regimes, AUC behaviors as a function of scan angle and number of projections sometimes differed from the anatomy-limited regime. For example, with a fixed scan angle, AUC generally decreased with the number of projections in the electronic-noise dominant regime. These results are intended to demonstrate the capabilities of the virtual trial framework, not to be used as optimization rules for DBT. The authors have demonstrated a novel simulation framework and tools for evaluating DBT systems in an objective, task-specific manner. This framework facilitates further investigation of image quality tradeoffs in DBT.

Localization of a Portion of an Endorectal Balloon for Prostate Image-Guided Radiation Therapy Using Cone-Beam Tomosynthesis: A Feasibility Study

To assess the feasibility of using cone-beam tomosynthesis (CBTS) to localize the air-tissue interface for the application of prostate image-guided radiation therapy using an endorectal balloon for immobilization and localization. A Feldkamp-David-Kress-based CBTS reconstruction was applied to selected sets of cone-beam computed tomography (CBCT) projection data to simulate volumetric imaging achievable from tomosynthesis for a limited range of scan angles. Projection data were calculated from planning CT images of 10 prostate cancer patients treated with an endorectal balloon, as were experimental CBCT projections for a pelvic phantom in two patients. More than 50 points at the air-tissue interface were objectively identified by an intensity-based interface-finding algorithm. Using three-dimensional point sets extracted from CBTS images compared with points extracted from corresponding CBCT images, the relative shift resulting from a reduced scan angle was determined. Because the CBCT and CBTS images were generated from the same projection data set, shift identified was presumed to be due to distortions introduced by the tomosynthesis technique. Scans of ≥60° were shown to be able to localize an air-tissue interface near the isocenter with accuracy on the order of a millimeter. The accuracy was quantified in terms of the mean discrepancy as a function of reconstruction angle. This work provides an understanding of the effect of scan angle used in localization of a portion of an endorectal balloon by means of CBTS. CBTS with relatively small scan angles is capable of accurately localizing an extended interface near the isocenter and may provide clinically relevant measurements to guide IGRT treatments while reducing imaging radiation to the patient.

Stochastic noise characteristics in matrix inversion tomosynthesis (MITS)

Matrix inversion tomosynthesis (MITS) uses known imaging geometry and linear systems theory to deterministically separate in-plane detail from residual tomographic blur in a set of conventional tomosynthesis ("shift-and-add") planes. A previous investigation explored the effect of scan angle (ANG), number of projections (N), and number of reconstructed planes (NP) on the MITS impulse response and modulation transfer function characteristics, and concluded that ANG = 20 degrees, N = 71, and NP = 69 is the optimal MITS imaging technique for chest imaging on our prototype tomosynthesis system. This article examines the effect of ANG, N, and NP on the MITS exposure-normalized noise power spectra (ENNPS) and seeks to confirm that the imaging parameters selected previously by an analysis of the MITS impulse response also yield reasonable stochastic properties in MITS reconstructed planes. ENNPS curves were generated for experimentally acquired mean-subtracted projection images, conventional tomosynthesis planes, and MITS planes with varying combinations of the parameters ANG, N, and NP. Image data were collected using a prototype tomosynthesis system, with 11.4 cm acrylic placed near the image receptor to produce lung-equivalent beam hardening and scattered radiation. Ten identically acquired tomosynthesis data sets (realizations) were collected for each selected technique and used to generate ensemble mean images that were subtracted from individual image realizations prior to noise power spectra (NPS) estimation. NPS curves were normalized to account for differences in entrance exposure (as measured with an ion chamber), yielding estimates of the ENNPS for each technique. Results suggest that mid- and high-frequency noise in MITS planes is fairly equivalent in magnitude to noise in conventional tomosynthesis planes, but low-frequency noise is amplified in the most anterior and posterior reconstruction planes. Selecting the largest available number of projections (N = 71) does not incur any appreciable additive electronic noise penalty compared to using fewer projections for roughly equivalent cumulative exposure. Stochastic noise is minimized by maximizing N and NP but increases with increasing ANG. The noise trend results for NP and ANG are contrary to what would be predicted by simply considering the MITS matrix conditioning and likely result from the interplay between noise correlation and the polarity of the MITS filters. From this study, the authors conclude that the previously determined optimal MITS imaging strategy based on impulse response considerations produces somewhat suboptimal stochastic noise characteristics, but is probably still the best technique for MITS imaging of the chest.

The Effect of Scanning Angle on Measured Reflectance and Tenderness Prediction in Beef Longissimus Thoracis Steaks

Near-infrared (NIR) reflectance spectroscopy has previously demonstrated potential to quantify tenderness and sensory attributes of meat. The objective of this study was to test the effect of scanning angle on visible/near-infrared (VNIR) spectral reflectance and the ability of reflectance spectra to predict tenderness of longissimus thoracis (LT) steaks. Two experiments were conducted to evaluate the effect of scanning angle configuration on steak reflectance. The first experiment included 60 steaks from two quality grades, aged for either 7 or 14 d, which were randomly assigned to two treatments in which the steak angles with respect to the light and sensor were changed. In the second experiment, 16 steaks from the two quality grades were scanned at six different angles. The Warner-Bratzler shear force (WBSF) was measured as a quantitative measure of tenderness. There were significant amplitude differences of up to 50% in the average reflectance spectra between the two treatments in experiment 1, and up to 200% difference between the reflectance spectra when the steak was tilted from 30 counterclockwise to 30 clockwise. First derivatives of the reflectance spectra also showed significant differences with respect to scanning angle. Chemometric models on VNIR spectra could predict only 19% of the variability in tenderness when the scanning angle was not considered. However, when individual models were developed for each scanning angle-aging group, the models accounted for 20% to 86% of the variability in tenderness. This study, with its limited data and tenderness ranges, showed that scanning angle is an important factor affecting the accuracy of reflectance-based tenderness models.

The Effect of Scan Angle on Target Localization Accuracy Using Digital Tomosynthesis

Purpose/Objective(s): To examine the effect of scan angle on target localization accuracy using on-board digital tomosynthesis (DTS) for breath-hold liver treatment. Material/Methods: 20 CBCT-localized fractions accumulated from liver radiation therapy treatments were studied retrospectively. To remove motion artifacts, image sets were acquired under breath-hold. The effect of scan angle, a key parameter for DTS, on target localization accuracy was evaluated for 10, 20 and 40 degree scan angles in both coronal and sagittal views. Assuming CBCT localization is the gold standard, the accuracy of the DTS technique is evaluated by the relative difference compared to the CBCT positioning. Localization accuracy was compared using two registration methods: bony anatomy based and soft tissue based alignment. Bony matching was performed by aligning the vertebral structures and ribs. Soft tissue matching was performed by aligning the liver boundaries, kidneys, and, when visible, the target. Results: The coronal and sagittal DTS had similar performance in aligning the target. Overall, the means and standard deviations for 40, 20 and 10 degree DTS were 0.2 +0.8 cm (40-cor.), 0.2 +0.8 cm (40-sag.), 0.1 +0.7cm (20-cor.), 0.2 +0.9 cm (20-sag.), 0.2 +0.9 cm (10-cor.), and 0.1 +0.7 cm (10-sag.). Figure 1. shows examples of DTS images at 10, 20, and 40 degree. Figure 2. plots the localization differences for the 10 and 40 degree DTS results in the lateral, vertical and longitudinal directions. Conclusion: The effect of scan angle on bony anatomy is minimal, and 10 degree DTS in either coronal or sagittal view is sufficient for bone based alignment. The visibility of liver boundaries was comparable with corresponding CBCT images on all DTS scans. However, detailed soft tissue contrast suffers when scan angle decreases from 40° to 10°. For BH liver treatment, the entire liver is clearly visible and can be used for soft tissue alignment. Partially supported by a Varian Medical Systems Research Grant

Radiometric normalization of sensor scan angle effects in optical remote sensing imagery

Radiometric distortions along the scan line, caused mainly by the atmosphere, reflection properties of the imaged surface objects, and topography are observed frequently in images acquired by optical remote‐sensing sensors, especially airborne sensors with a wide field of view. In practical applications, such as classification or mosaicking of image data, a relative correction or normalization of these radiometric distortions is needed. Therefore, the goal of this paper is to derive a relative correction algorithm for multispectral line scanner images, which allows the spectral radiance values for different scan angles to be converted to radiance values of a defined reference scan angle. Under the simplifying assumption of complete diffuse reflectors, these radiometric distortions are modelled using a linear equation between the radiances of a pair of scan angles for each class of surface objects separately. A linear regression, applied to all these equations, results in a linear model for the radiance correction, a new empirical radiometric correction method, which is a generalization of earlier proposed strictly additive or multiplicative models. The proposed method is based solely on the digital image data. So, no additional information or user interaction is required, and the method is fully automatic. Applications for data acquired with the airborne multispectral scanner DAEDALUS AADS 1268 ATM show the effectiveness and potential of the proposed method especially for mosaicking and classification purposes.