Effect of disparity and viewing ambient illumination on stereoscopic viewing: An eye movement approach

Researchers have found that factors related to viewing content and viewing environment could influence viewers' stereoscopic viewing experiences. In this paper, the effect of both disparity and viewing ambient illumination condition on stereoscopic viewing was investigated by using an eye movement approach. The eye movement responses to random dot stereograms (RDS) stimuli in stereoscopic viewing were studied by performing a fusion range measurement experiment involving a judgment task. The fusion ranges under two ambient illumination conditions, eye movement responses to RDS stimuli and effects of disparity on eye movement parameters, were analyzed, respectively. The experimental results showed that fusion range under two ambient illumination conditions were different, and changes of eye movement parameters were different among various disparities when ambient illumination conditions varied. As a result, in order to improve viewers' viewing experiences when viewing different 3D contents, the arrangement of viewing ambient illumination conditions and the selection of disparity should be appropriately considered. The findings in this paper provide guidelines to reasonably arrange the viewing ambient illumination condition and efficiently produce healthy disparity in stereoscopic viewing.     

Soil surface illumination at micro-relief scale and soil BRDF data collected by a hyperspectral camera

The results of the paper draw attention to the fact that the hyperspectral image of soil surface at micro-relief scale may display variation in the soil spectral shape due to illumination conditions of the surface. The image of an extremely rough cultivated soil surface, very deeply ploughed, was obtained by a hyperspectral camera, in the range of 0.4–1.0 μm with 0.67–0.74 nm spectral resolution. It was found that the soil reflectance spectra of the studied surface, illuminated by the direct sunbeams, are clearly convex with distinct absorption features. Furthermore, the soil normalized reflectance spectra were used to distinguish the subtlety of the analysed shaded soil spectra shape. They show that depressions caused by the absorption features of O₂ and H₂O, contained in the atmosphere above directly illuminated soil fragments, transform into peaks, if the same soil is deeply shaded.     

Influence of soil surface roughness on soil bidirectional reflectance

The non-Lambertian behaviour of soil surfaces depends on its roughness at micro-scale and larger scales, as well as on the incident angle of the direct solar beam on the surface. A geometrical model, taking into account the diffuse as well as the specular component of energy leaving soil surfaces in the visible and near-infrared, is used in the paper to describe the influence of soil surface roughness, caused by soil aggregates or soil clods, on the soil bidirectional reflectance distribution. A rough soil surface in the model is simulated by equalsized opaque spheroids lying on a horizontal surface. The model was tested in outdoor conditions on artificially formed soil surfaces made of two spectrally different soil materials: a mineral loam, and a loam with high organic matter content. The spectral data were measured by a field radiometer in the three SPOT (HRV) bands. The model predicts that at specific illumination conditions, soils surfaces with the highest roughness, expressed by the minimum distances between soil aggregates, can show lower variation of reflectance in the view zenith angle function than soil surfaces of a lower roughness.     

Estimating surface air temperatures,from Meteosat land surface temperatures,using an empirical solar zenith angle model

Temperature values derived from Meteosat are an indication of emitted long-wave radiation, and are not a true indication of ambient air temperature. The authors believe that Solar Zenith Angle (SZA) can be used as a proxy for solar energy reaching the ground surface, and its subsequent effects upon the land surface temperature detected by Meteosat. Raw satellite temperatures often overestimate the actual screen temperature during the day, and underestimate at night. By using a statistical model which relates Meteosat and WMO screen temperature deviations, and SZA values, it has been possible to generate a correction algorithm which minimizes these differences. The algorithm generates a new proxy value, being a simulated ambient (screen) air temperature. The algorithms achieve an accuracy of within 3 C for over 70% of the Meteosat temperatures processed. The operational use of this algorithm requires only the raw Meteosat temperature value, and the SZA. Such temperature corrections are useful for a wide range of environmental monitoring applications. An example is in the field of vector-borne disease modelling which requires proxies for temperature across large regions, and where more conventional meteorological stations are inadequate.     

Importance sampling of products from illumination and BRDF using spherical radial basis functions

In this paper, a new approach for the importance sampling of products from a complex high dynamic range (HDR) environment map and measured bidirectional reflectance distribution function (BRDF) data using spherical radial basis functions (SRBFs) is presented. In the pre-process, a complex HDR environment map and measured BRDF data are transformed into a scattered SRBF representation by using a non-uniform and non-negative SRBF fitting algorithm. An initial guess is determined for the fitting operation. In the run-time rendering process, after the product of the two SRBFs is evaluated, this is used to guide the number of samples. The sampling is done by mixing samples from the various “product” SRBFs using multiple importance sampling. Hence, the proposed approach efficiently renders images with multiple HDR environment maps and measured BRDFs.     

Mapping surface roughness and soil moisture using multi-angle radar imagery without ancillary data

The Integral Equation Model (IEM) is the most widely-used, physically based radar backscatter model for sparsely vegetated landscapes. In general, IEM quantifies the magnitude of backscattering as a function of moisture content and surface roughness, which are unknown, and the known radar configurations. Estimating surface roughness or soil moisture by solving the IEM with two unknowns is a classic example of under-determination and is at the core of the problems associated with the use of radar imagery coupled with IEM-like models. This study offers a solution strategy to this problem by the use of multi-angle radar images, and thus provides estimates of roughness and soil moisture without the use of ancillary field data. Results showed that radar images can provide estimates of surface soil moisture at the watershed scale with good accuracy. Results at the field scale were less accurate, likely due to the influence of image speckle. Results also showed that subsurface roughness caused by rock fragments in the study sites caused error in conventional applications of IEM based on field measurements, but was minimized by using the multi-angle approach.     

Effect of surface roughness on liquid property measurements using mechanically oscillating sensors

The resonant frequency and quality factor Q of a liquid immersed magnetoelastic sensor are shown to shift linearly with the liquid viscosity and density product. Measurements using different grade oils, organic chemicals, and glycerol-water mixtures show that the surface roughness of the sensor in combination with the molecular size of the liquid play important roles in determining measurement sensitivity, which can be controlled through adjusting the surface roughness of the sensor surface. A theoretical model describing the sensor resonant frequency and quality factor Q as a function of liquid properties is developed using a novel equivalent circuit approach. Experimental results are in agreement with theory when the liquid molecule size is larger than the average surface roughness. However, when the molecular size of the liquid is small relative to the surface roughness features molecules are trapped, and the trapped molecules act both as a mass load and viscous load; the result is higher viscous damping of the sensor than expected.     

Investigating the potential for soil moisture and surface roughness monitoring in drylands using ERS SAR data

Multitemporal ERS-1 and ERS-2 SAR data were acquired for northern Jordan between 1995 and 1997 to investigate changes in the backscatter coefficients of a range of typical desert land surfaces. The changes in backscatter found were ascribed to variations in surface soil moisture, and changes in surface roughness caused by a range of natural and anthropogenic factors. Data collected from monitored sites were input into the Integral Equation Model (IEM). The model outputs were strongly correlated with observed backscatter coefficients (r ²=0.84). The results show that the successful monitoring of soil moisture in these environments is strongly dependent on the surface roughness. On surfaces with RMS height 0.5 cm, the sensitivity of the backscatter coefficient to changes in surface microtopography did not allow accurate soil moisture estimation. Microtopographic change on rougher surfaces has less influence on the backscatter coefficient, and the probability of soil moisture estimation from SAR imagery is greater. These results indicate that knowledge of the surface conditions (both in terms of surface roughness and geomorphology) is essential for accurate soil moisture monitoring, whether in a research or operational context. The potential benefits of these findings are discussed in the context of the Jordan Badia Research and Development Project.     

Modulation of viewing angle on an LCD surface through backlight optics

Abstract— A backlight unit (BLU) that varies the viewing angle from the top to the bottom surface of a transmissive LCD screen has been developed through the design and fabrication of microstructures on a light‐guide plate (LGP). An array of taper prisms has been designed and fabricated on the back surface of the LGP, which resulted in the variation of 29° in the angular distribution of the luminance of the backlight from the top sector to the bottom sector of its surface. This characteristic is employed to modulate the viewing angle of the LCD from the top of the screen to the bottom of the screen for special applications.     

Determination of sea surface temperature at large observation angles using an angular and emissivity-dependent split-window equation

This paper proposes an angular and emissivity-dependent split-window equation that permits the determination of the sea surface temperature (SST) to a reasonable level of accuracy for any observation angle, including large viewing angles at the image edges of satellite sensors with wide swaths. This is the case of the MODIS radiometer both on EOS Terra/Aqua platforms, with observation angles of up to 65° at the surface, for which the split-window equation has been developed in this study. The algorithm takes into account the angular dependence of both the atmospheric correction (due to the increase of the atmospheric optical path with angle) and the emissivity correction (since sea surface emissivity (SSE) decreases with observation angle). Angular-dependent coefficients have been estimated for the atmospheric terms, and also an explicit dependence on the SSE has been included in the algorithm, as this parameter has values different to a blackbody surface for off-nadir angles, the SSEs also being dependent on surface wind speed. The proposed algorithm requires as input data at-sensor brightness temperatures for the split-window bands (31 and 32 of MODIS), the observation angle at each pixel, an estimate of the water vapor content (which is provided by the MODIS MOD07/MYD07 products) and accurate SSE values for both channels. The preliminary results show a good agreement between SSTs estimated by the proposed equation for off-nadir viewings of MODIS-Terra images and in situ SST measurements, with a root-mean square error (RMSE) of about ± 0.3 K, for which the MODIS SST product gives an RMSE larger than ± 0.7 K.     

Influence of the canopy BRDF characteristics and illumination conditions on the retrieval of solar-induced chlorophyll fluorescence

The Fraunhofer line discrimination (FLD) principle is the main approach used for the retrieval of solar-induced chlorophyll fluorescence (SIF). The basic assumption of the FLD principle is that the apparent reflectance spectra without SIF in-filling are smooth in the region of the absorption bands. However, in fact, this assumption is not valid due to the so-called ‘direct radiation in-filling’ effect caused by the nonlinear contribution of direct and diffuse radiation at the oxygen absorption bands, which are widely used for ground-based SIF retrieval. In this study, we first analysed the physical mechanism of the direct radiation in-filling effect on the oxygen absorption bands and found that the bias in the SIF retrieval caused by the direct radiation in-filling effect at the oxygen-A (O₂-A) band was less than 20% based on the use of a simulated data set. Second, we established a simple correction model of the direct radiation in-filling effect. We found that the direct radiation in-filling effect at the O₂-A band was directly proportional to the difference between the reflectance of the direct and diffuse radiation, and that the coefficient of proportionality was well correlated with the diffuse-to-global radiation ratio in the form of a quadratic function, with a coefficient of determination (R²) of 0.97. Finally, the model was validated using both simulated and field data sets. The validation results show that the bias in the SIF retrieval caused by the direct radiation in-filling effect can be efficiently corrected using the model proposed in this article. This study thus provides a possible approach to estimating and correcting for the direct radiation-infilling effect using prior knowledge of the bidirectional reflectance distribution function characteristics of direct and diffuse radiation for specific targets.     

Sensitivity of bistatic scattering to soil moisture and surface roughness of bare soils

The sensitivity of bistatic scattering coefficient σ° to soil moisture content (SMC) and surface roughness was investigated by means of model simulations of the incoherent scattered fields performed with the advanced integral equation model (AIEM) and the second order small perturbation model (SPM). The study was performed by simulating scattering on the whole upper half space, for different values of incident angles. The achieved results, represented as maps of σ° as a function of azimuth and zenith angles, were evaluated by means of a quality index which takes into consideration the effect of roughness on SMC measurement. The sensitivity analysis has pointed out that for measuring SMC a bistatic observation, by itself or combined with the monostatic one, can make appreciable improvements with respect to classical monostatic radar. Appendix A contains the AIEM formulas corrected for several typographical errors present in the specific literature.     

Passive microwave sensing of soil moisture content: The effects of soil bulk density and surface roughness

Microwave radiometric measurements over bare fields of different surface roughness were made at frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz to study the frequency dependence, as well as the possible time variation, of surface roughness. An increase in surface roughness was found to increase the brightness temperature af soils and reduce the slope of regression between brightness temperature and soil moisture content. The frequency dependence of the surface roughness effect was relatively weak when compared with that of the vegetation effect. Radiometric time-series observations over a given field indicate that field surface roughness might gradually diminish with time, especially after a rainfall or irrigation. The variation of surface roughness increases the uncertainty of remote soil moisture estimates by microwave radiometry. Three years of radiometric measurements over a test site revealed a possible inconsistency in the soil bulk density determination, which is an important factor in the interpretation of radiometric data.     

Effect of tool vibrations on surface roughness during lathe dry turning process

Choice of optimized cutting parameters is very important to control the required surface quality. In fact, the difference between the real and theoretical surface roughness can be attributed to the influence of physical and dynamic phenomena such as: built-up edge, friction of cut surface against tool point and vibrations. The focus of this study is the collection and analysis of surface roughness and tool vibration data generated by lathe dry turning of mild carbon steel samples at different levels of speed, feed, depth of cut, tool nose radius, tool length and work piece length. A full factorial experimental design (288 experiments ) that allows to consider the three-level interactions between the independant variables has been conducted. Vibration analysis has revealed that the dynamic force, related to the chip-thickness variation acting on the tool, is related to the amplitude of tool vibration at resonance and to the variation of the tool's natural frequency while cutting. The analogy of the effect of cutting parameters between tool dynamic forces and surface roughness is also investigated. The results show that second order interactions between cutting speed and tool nose radius, along with third-order interaction between feed rate, cutting speed and depth of cut are the factors with the greatest influence on surface roughness and tool dynamic forces in this type of operation and parameter levels studied. The analysis of variance revealed that the best surface roughness condition is achieved at a low feed rate (less than 0.35 mnt/rev), a large tool nose radius (1.59 mm) and a high cutting speed (265 m/min and above). The results also show that the depth of cut has not a significant effect on surface roughness, except when operating within the built-up edge range. It is shown that a correlation between surface roughness and tool dynamic force exist only when operating in the built-up edge range. In these cases, built-u edge formation deteriorates surface roughness and increases dynamic forces acting on the tool. The effect of built-up edge formation on surface roughness can be minimized by increasing depth of cut and increasing tool vibration. Key words:design of experiments, lathe dry turning operation, full factorial design, surface roughness, measurements, cutting parameters, tool vibrations.     

The asymptotic behaviour,the angles of departure,and the angles of approach,of the characteristic frequency loci

In algebraic function theory, there is a well established method which uses ‘Newton's diagram’ to find the series expansions of an algebraic function q(x) in the neighbourhood of a point x₀ . In this paper it is shown how, for a linear, time-invariant, multi-variable feedback system, this method can be used to find :

(i) the asymptotic behaviour of the characteristic frequency loci (multivariable root loci) ;

(ii) the angles of departure of the characteristic frequency loci from the open-loop poles ; and

(iii) the angles of approach of the characteristic frequency loci to the finite zeros of such a system.     

Monitoring the tool wear,surface roughness and chip formation occurrences using multiple sensors in turning

Tool wear, chip formation and surface roughness of workpiece under different cutting conditions have been investigated in machining using acoustic emission (AE) and vibration signature in turning. The investigation has shown that the AE and vibration components can effectively respond to the different occurrences in turning including tool wear and surface roughness. The AE has shown a very significant response to the tool wear progression whereas the resultant vibration (V) represented the surface roughness in turning. The vibration components V_x, V_y and V_z described the chip formation type and are found to have the most significant response to the change of feed, depth of cut and cutting speed respectively. The amplitude of vibration components, V_x, V_y and V_z increased with the increase of feed rate, depth of cut and cutting speed respectively. Even though the frequency of different signal components fluctuated at the different stages of tool wear and at different cutting conditions, the frequency of vibration components was always within a band of 98–40 kHz, and the AE has varied between 51 kHz and 620 kHz.     

Optimisation of surveillance camera site locations and viewing angles using a novel multi-attribute,multi-objective genetic algorithm: A day/night anti-poaching application

The optimisation of surveillance and detection systems comprised of specialised cameras is a well-known problem in the operations research literature. In these problems, the aim is to locate optimal camera sites so that their combined coverage with respect to some area of interest – called a cover zone – is maximised. The standard approach is to maximise cover with respect to a single cover zone, and to consider either cameras providing rotational (360°) cover, or cameras fixed to a specific direction and with visibility limited to within the camera's field-of-view. The Rhino Pride Foundation in South Africa required the optimisation of a camera surveillance system for a new protected area. Their coverage requirements were, however, beyond what has been previously encountered in the literature. Four covering objectives over three separate cover zones were to be maximised, while the system was to be optimised for rotational cover during the day, and some cameras would be required to be fixed towards a high-risk zone at night and limited to their field-of-view. A novel multi-attribute genetic algorithm based on the popular NSGA-II was developed for this purpose. Various solutions were provided to and considered by the Rhino Pride Foundation, and the final selected solution resulted in camera site locations providing high-quality cover with respect to all the covering objectives, while requiring fewer cameras than initially expected – resulting in significant cost savings and reduced future maintenance and upgrade requirements. The solution approach presented here may be applied to other site-selection problems with similar coverage requirements, including military radar and weapon systems, and wildfire detection systems.     

Estimation of cutting forces and surface roughness for hard turning using neural networks

Metal cutting mechanics is quite complicated and it is very difficult to develop a comprehensive model which involves all cutting parameters affecting machining variables. In this study, machining variables such as cutting forces and surface roughness are measured during turning at different cutting parameters such as approaching angle, speed, feed and depth of cut. The data obtained by experimentation is analyzed and used to construct model using neural networks. The model obtained is then tested with the experimental data and results are indicated.     

Analysis of TerraSAR-X data sensitivity to bare soil moisture, roughness, composition and soil crust

Soils play a key role in shaping the environment and in risk assessment. We characterized the soils of bare agricultural plots using TerraSAR-X (9.5 GHz) data acquired in 2009 and 2010. We analyzed the behavior of the TerraSAR-X signal for two configurations, HH-25° and HH-50°, with regard to several soil conditions: moisture content, surface roughness, soil composition and soil-surface structure (slaking crust).The TerraSAR-X signal was more sensitive to soil moisture at a low (25°) incidence angle than at a high incidence angle (50°). For high soil moisture (> 25%), the TerraSAR-X signal was more sensitive to soil roughness at a high incidence angle (50°) than at a low incidence angle (25°).The high spatial resolution of the TerraSAR-X data (1 m) enabled the soil composition and slaking crust to be analyzed at the within-plot scale based on the radar signal. The two loamy-soil categories that composed our training plots did not differ sufficiently in their percentages of sand and clay to be discriminated by the X-band radar signal.However, the spatial distribution of slaking crust could be detected when soil moisture variation is observed between soil crusted and soil without crust. Indeed, areas covered by slaking crust could have greater soil moisture and consequently a greater backscattering signal than soils without crust.