Illumination Cone Research Articles

Predicted effectiveness of EnChroma multi-notch filters for enhancing color perception in anomalous trichromats

EnChroma filters are aids designed to improve color vision for anomalous trichromats. Their use is controversial because the results of lab-based assessments of their effectiveness have so far largely failed to agree with positive anecdotal reports. However, the effectiveness of EnChroma filters will vary depending on the conditions of viewing, including whether the stimuli are broadband reflective surfaces or colors presented on RGB displays, whether illumination spectra are broadband or narrowband, the transmission spectra of particular filters, and the cone spectral sensitivity functions of the observer. We created a model of anomalous trichromatic color vision to predict the effects of EnChroma filters on the color signals impaired in anomalous trichromacy. Using the model we varied illumination, filter type and observer cone sensitivity functions, and tested the effect of presenting colors as broadband reflective surfaces or on RGB displays. We also used hyperspectral images to assess the impact of the filters on anomalous trichromats’ color vision for natural scenes. Model results predicted that the filters should be broadly effective at enhancing anomalous trichromats’ equivalent to L/(L + M) chromatic contrasts under a range of viewing conditions, but are substantially more effective for deuteranomals than for protanomals. The filters are predicted to be more effective for broadband reflective surfaces presented under broadband illuminants than for surfaces presented under narrowband illuminants or for colors presented on RGB displays. Since the potential impacts of contrast adaptation and perceptual learning are not considered in the model, it needs to be empirically validated. Results of empirical tests of the effects of EnChroma filters on deuteranomalous color vision in comparison with model predictions are presented in an accompanying paper (Somers et al., in prep.).

Origin of the super-resolution of microsphere-assisted imaging

Theoretical explanation of the super-resolution imaging by contact microspheres created a point of attraction for nanoimaging research during the last decade with many models proposed, yet its origin remains largely elusive. Using a classical double slit object, the key factors responsible for this effect are identified by an ab initio imaging model comprising object illumination, wave scattering, and image reconstruction from the diffracted far fields. The scattering is found by a full-wave solution of the Maxwell equations. The formation of super-resolved images relies on coherent effects, including the light scattering into the waves circulating inside the microsphere and their re-illumination of the object. Achieving the super-resolution of the double slit requires a wide illumination cone as well as a deeply sub-wavelength object-to-microsphere separation. The resultant image has a significantly better resolution as compared to that from the incoherent imaging theory.

Experimental Validation of Shifted Position-Diffuse Reflectance Imaging (SP-DRI) on Optical Phantoms.

Numerous diseases such as hemorrhage, sepsis or cardiogenic shock induce a heterogeneous perfusion of the capillaries. To detect such alterations in the human blood flow pattern, diagnostic devices must provide an appropriately high spatial resolution. Shifted position-diffuse reflectance imaging (SP-DRI) has the potential to do so; it is an all-optical diagnostic technique. So far, SP-DRI has mainly been developed using Monte Carlo simulations. The present study is therefore validating this algorithm experimentally on realistic optical phantoms with thread structures down to 10 μm in diameter; a SP-DRI sensor prototype was developed and realized by means of additive manufacturing. SP-DRI turned out to be functional within this experimental framework. The position of the structures within the optical phantoms become clearly visible using SP-DRI, and the structure thickness is reflected as modulation in the SP-DRI signal amplitude; this performed well for a shift along the x axis as well as along the y axis. Moreover, SP-DRI successfully masked the pronounced influence of the illumination cone on the data. The algorithm showed significantly superior to a mere raw data inspection. Within the scope of the study, the constructive design of the SP-DRI sensor prototype is discussed and potential for improvement is explored.

Holographic point source for digital lensless holographic microscopy.

A holographic point source (HPS) developed for digital lensless holographic microscopy (HPS-DLHM) is presented. The HPS is an off-axis phase transmission hologram of an experimental micrometer pinhole recorded on a photopolymer holographic film. An amplitude division interferometer, adjusted to operate at maximum diffraction efficiency, has been employed to record the hologram. The results of HPS-DLHM have been contrasted with the results obtained via conventional DLHM, and the two techniques were found to give similar measurements. Compared with conventional pinhole-based DLHM illumination, our cost-effective proposal provides increased mechanical stability, the possibility of wider spherical illumination cones, and shorter reconstruction distances. These superior features pave the way to applying this quantitative phase imaging (QPI) technique in biomedical and telemedicine applications. The imaging capabilities of our HPS-DLHM proposal have been tested by using an intricate sample of a honeybee leg, a low-absorption sample of epithelial cheek cells, a 1951 USAF test target, and smeared human erythrocytes.

Minimum-dose phase-contrast tomography by successive numerical optical sectioning employing the aberration-corrected STEM and a pixelated detector

Aberration correction combined with a pixelated detector enable atomic-resolution phase-contrast imaging in the scanning transmission electron microscope (STEM) using all elastically scattered electrons within the illumination cone. The review describes this possibility in detail revisiting the image formation in the STEM on a fundamental quantum-mechanical treatment of electron scattering within the object and the effect of the lenses on the electron wave. Describing electron scattering by means of scattering amplitudes enables a straightforward derivation of a) the reciprocity theorem, b) the optical theorem of electron scattering, and c) the precise formulation of the image intensity distribution in the STEM for different modes of operation. The second part of the review describes in detail a novel method for obtaining pure phase-contrast images in the STEM using the integrated differential phase-contrast (IDPC) procedure. The incorporation of a chromatic (Cc) and spherically (Cs) corrected objective lens and a pixelated detector in the STEM combined with numerical through-focusing enables optical sectioning with atomic 3D resolution of thick objects with about the same dose as that for a 2D object, at least in principle. Numerical simulations of the IDPC transfer function and the point spread function for the focal plane and several reconstructed defocused planes demonstrate the feasibility of the method.

Deep Learning Autoencoder for Single Specimen Face Remembrance

This paper aims learning powerful picture portrayal for single preparing test per individual face acknowledgment. Propelled at achievement of deep learning (DL) within picture portrayal, this article proposes a regulated autoencoder (AE), which is another sort of edifice obstruct for deep structures. There are 2 highlights particular our managed AE from standard AE. In the initial place, we uphold the countenances by variations to be delineated using the standard substance of the diacritic, as example, frontispiece having unbiased appearance and typical enlightenment, further, we uphold features comparing to an analogous diacritic to be comparable. Therefore, our administered autoencoder separates the highlights which are strong to fluctuations in light, articulation, impediment, and present, and encourages the face acknowledgment. We heap such regulated AEs to achieve the deep design and utilize it for separating highlights in picture portrayal. Exploratory corollary on the Extended Yale B (Athinodoros Georghiades, et al., 2001. From few to many: Illumination cone models for face recognition under variable lighting and pose. PAMI, 23(6), pp.643–660), informational collections show that by coupling with the normally utilized inadequate portrayal based grouping, our stacked managed AEs-based face portrayal essentially beats the usually utilized picture portrayals in single example per individual face acknowledgment, and it attains lofty cognizance precision conflicted and alternative DL prototypes, which includes the deep Lambertian organize, incite of appreciably fewer preparing detail and without area data. Additionally, regulated AE can correspondingly be utilized for face check that additionally shows its acceptability for frontispiece rendering.

Luminescent surfaces with tailored angular emission for compact dark-field imaging devices

Dark-field microscopy is a standard imaging technique widely employed in biology that provides high image contrast for a broad range of unstained specimens1. Unlike bright-field microscopy, it accentuates high spatial frequencies and can therefore be used to emphasize and resolve small features. However, the use of dark-field microscopy for reliable analysis of blood cells, bacteria, algae, and other marine organisms often requires specialized, bulky microscope systems, and expensive additional components, such as dark-field-compatible objectives or condensers2,3. Here, we propose to simplify and downsize dark-field microscopy equipment by generating the high-angle illumination cone required for dark field microscopy directly within the sample substrate. We introduce a luminescent photonic substrate with a controlled angular emission profile and demonstrate its ability to generate high-contrast dark-field images of micrometre-sized living organisms using standard optical microscopy equipment. This new type of substrate forms the basis for miniaturized lab-on-chip dark-field imaging devices, compatible with simple and compact light microscopes.

Constraints on the Collimated X-ray Emission of SS 433 from the Reflection on Molecular Clouds

We calculate X-ray signal that should arise due to reflection of the putative collimated X-ray emission of the Galactic supercritical accretor SS 433 on molecular clouds in its vicinity. The molecular gas distribution in the region of interest has been constructed based on the data of the BU-FCRAO GRS in $^{13}$CO $J=1\rightarrow0$ emission line, while the collimated emission was assumed to be aligned with the direction of the relativistic jets, which are continuously launched by the system. We consider all the available $Chandra$ observations covering the regions possibly containing the reflection signal and put constraints on the apparent face-on luminosity of SS 433 above 4 keV. No signatures of the predicted signal have been found in the analysed regions down to a 4-8 keV surface brightness level of $\sim 10^{-11}$ erg/s/cm$^2$/deg$^2$. This translates into the limit on the apparent face-on 2-10 keV luminosity of SS 433 $L_{X,2-10}\lesssim 8\times10^{38}$ erg/s, provided that the considered clouds do fall inside the illumination cone of the collimated emission. This, however, might not be the case due to persisting uncertainty in the line-of-sight distances to SS 433 $d_{SS433}$ (4.5-5.5 kpc) and to the considered molecular clouds. For half-opening angle of the collimation cone larger than or comparable to the amplitude of the jets' precession ($\approx21\deg$), the stringent upper limit quoted above is most relevant if $d_{SS433}<5$ kpc, provided that the kinematic distances to the considered molecular clouds are sufficiently accurate. Dropping the last assumption, a more conservative constraint is $L_{X,2-10}\lesssim10^{40}$ erg/s for $d_{SS433}=4.65-4.85$ kpc (and yet worse outside this range). We conclude that SS 433 is not likely to belong to the brightest ultraluminous X-ray sources if it could be observed face-on, unless its X-ray emission is highly collimated. (Abridged)

Implication of Illumination Beam Geometry on Stray Light and Bandpass Characteristics of Diode Array Spectrometer

This paper describes spectral stray light measurements of diode array spectrometers and, in particular, the dependence of stray light and bandpass properties on the illumination beam geometry. The effects of underfilling and overfilling the nominal field of view of the instrument are presented. Our measurements showed that the line spread function of a commercially available miniature spectrometer module having a fiber optic entrance with 0.22 nominal numerical aperture can depend on fiber illumination cone apex angle up to $40^\circ$ , which is well above the $25^\circ$ nominal acceptance cone apex angle of the fiber. The bandpass width and amount of stray light inside the spectrometer increased proportionally with the illumination cone angle. Spectral stray light measurements with different setups gave consistent and repeatable results for similar illumination geometries. Care should be taken to ensure that illumination geometry during spectral stray light characterization of a spectrometer matches the conditions during target measurements for which the spectral stray light corrections are applied. The impact of illumination geometry during stray light characterization depends on the target signal and particular application. Photochemical reflectance index (PRI) and normalized difference vegetation index (NDVI) of a hemiboreal birch forest are used as contrasting examples in this paper. Compared to natural variability, the relative impact on PRI exceeds that of NDVI by 10 times.

Exploring the theoretical basis and limitations of cryo-STEM tomography for thick biological specimens.

Scanning transmission electron microscope (STEM) imaging has recently been applied to the cryo-tomography of thick biological specimens. As previously shown for plastic sections, STEM has a number of advantages for cryo-imaging compared to conventional wide-field TEM imaging. STEM is insensitive to phase coherence and is therefore suitable for much thicker specimens than TEM. Imaging in focus, with a long depth of field, also circumvents the complications of an oscillatory contrast transfer function and missing information at low spatial frequencies. Moreover the image signal represents a quantitative measurement of the electron scattering pixel by pixel, so that absolute intensities can be interpreted in terms of material properties in the specimen. Resolution, however, is undoubtedly compromised for thick samples, especially in the regime of multiple elastic scattering. In this work we address the specific issues that arise in cryo-tomography of thick biological specimens. We formulate an imaging model based on a Boltzmann transport equation, complemented by Monte Carlo simulations. Using these theoretical tools, we identify conditions for image acquisition that will be compatible with the basic presumption of tomographic reconstruction, i.e., that for a given composition the imaging signal varies monotonically with thickness. For optimal resolution, contrast, and signal strength, we propose to generalize the on-axis bright field detector to collect at angles well beyond the illumination cone. Our results justify the generation of 3D images for micron thicknesses and beyond.

Diffractive digital lensless holographic microscopy with fine spectral tuning

We experimentally demonstrate an all-diffractive optical setup for digital lensless holographic microscopy with easy wavelength line selection and micrometric resolution. In the proposed system, an ultrashort laser pulse is focused with a diffractive lens (DL) onto a pinhole of diameter close to its central wavelength to achieve a highly spatially coherent illumination cone as well as a spectral line with narrow width. To scan the complete spectrum of the light source the DL is displaced with respect to the pinhole plane. The proposed microscopy setup allows us to spectrally separate contributions from different sections of a sample, which may be attractive for several applications in life sciences.

A robust real-time algorithm for facial shape recovery from a single image containing cast shadow under general, unknown lighting

It is difficult to find a non-iterative solution for statistical shape from shading (SFS) for a single image containing cast shadow under unknown, arbitrary light conditions. This is because it is not trivial to find a mapping from a convex cone in the image space to a point in the depth space. To find a non-iterative solution for the statistical SFS, which has not been done yet to our knowledge, we show that it is possible to approximate a cone of images (illumination cone) to a polytope by a nonlinear function, which is a transform from Cartesian coordinates to hyperspherical coordinates. The images of a subject form a convex cone in the image space, and it can be better to use the direction of an image in hyperspherical coordinates as an input feature for the mapping rather than the image itself. The maximum error occurs on one of the vertices of the polytope if we choose the objective function to be the squared error of a linear function in the hyperspherical space. Hence, we can solve the least square problem using the cost only for the vertices. In deriving the solution, we use the generalized Rayleigh quotient, canonical correlation analysis (CCA), and prior information on input images, to reduce the solution space and improve 3-D reconstruction performance. In experiments, the proposed scheme performs robustly under light variations, and is fast enough for real-time applications.

Angle-and polarization-dependent collective excitation of plasmonic nanoarrays for surface enhanced infrared spectroscopy

Our recent work has showed that diffractively coupled nanoplasmonic arrays for Fourier transform infrared (FTIR) microspectroscopy can enhance the Amide I protein vibrational stretch by up to 10(5) times as compared to plain substrates. In this work we consider computationally the impact of a microscope objective illumination cone on array performance. We derive an approach for computing angular- and spatially-averaged reflectance for various numerical aperture (NA) objectives. We then use this approach to show that arrays that are perfectly optimized for normal incidence undergo significant response degradation even at modest NAs, whereas arrays that are slightly detuned from the perfect grating condition at normal incidence irradiation exhibit only a slight drop in performance when analyzed with a microscope objective. Our simulation results are in good agreement with microscope measurements of experimentally optimized periodic nanoplasmonic arrays.

Identifying faces across variations in lighting

Humans have the ability to identify objects under varying lighting conditions with extraordinary accuracy. We investigated the behavioral aspects of this ability and compared it to the performance of the illumination cones (IC) model of Belhumeur and Kriegman [1998]. In five experiments, observers learned 10 faces under a small subset of illumination directions. We then tested observers' recognition ability under different illuminations. Across all experiments, recognition performance was found to be dependent on the distance between the trained and tested illumination directions. This effect was modulated by the nature of the trained illumination directions. Generalizations from frontal illuminations were different than generalizations from extreme illuminations. Similarly, the IC model was also sensitive to whether the trained images were near-frontal or extreme. Thus, we find that the nature of the images in the training set affects the accuracy of an object's representation under variable lighting for both humans and the model. Beyond this general correspondence, the microstructure of the generalization patterns for both humans and the IC model were remarkably similar, suggesting that the two systems may employ related algorithms.

Face Recognition Using 3-D Models: Pose and Illumination

Unconstrained illumination and pose variation lead to significant variation in the photographs of faces and constitute a major hurdle preventing the widespread use of face recognition systems. The challenge is to generalize from a limited number of images of an individual to a broad range of conditions. Recently, advances in modeling the effects of illumination and pose have been accomplished using three-dimensional (3-D) shape information coupled with reflectance models. Notable developments in understanding the effects of illumination include the nonexistence of illumination invariants, a characterization of the set of images of objects in fixed pose under variable illumination (the illumination cone), and the introduction of spherical harmonics and low-dimensional linear subspaces for modeling illumination. To generalize to novel conditions, either multiple images must be available to reconstruct 3-D shape or, if only a single image is accessible, prior information about the 3-D shape and appearance of faces in general must be used. The 3-D Morphable Model was introduced as a generative model to predict the appearances of an individual while using a statistical prior on shape and texture allowing its parameters to be estimated from single image. Based on these new understandings, face recognition algorithms have been developed to address the joint challenges of pose and lighting. In this paper, we review these developments and provide a brief survey of the resulting face recognition algorithms and their performance

From 2D to 3D: Using Illumination Cones to Build 3d Face Model

To solve the problem derivate by lighting condition and position of the camera, a new method using illumination cones to build 3d face model has been proposed. Due to illumination variability, the same object can show dramatic difference even as being viewed in fixed pose. To handle this variability, an object recognition system must employ a representation that is either invariant to, or can model this variability. The proposed technique presents an appearance-based method for modeling the variability due to illumination in the images of objects. The method differs from past appearance-based methods. Evenmore, a small set of training images is used to generate a representation that the illumination cone models the complete set of images of an object with Lambertian reflectance surface under a combination of arbitrary point light sources at infinity. After building up the illumination cones, researches focus on how to present the 3d model of the face. Combining illumination and texture feature to build up 3d model of the face make it easy solving the problem in recognition of face under different pose.

On‐line analysis of chrome–iron ores on a conveyor belt using x‐ray fluorescence analysis

AbstractWe describe the method for and results of the application of an EDXRF on‐line analyzer for the analysis and quality testing of chrome–iron ores. For this task we used a BSI‐2000 analyzer for measurement of lumpy material being transported by a conveyor belt. The task of fully automated quantitative analysis of material on a conveyor belt is not very simple, as the results of measurements should not depend significantly on many factors, such as the distance to the measured material, the lump size, unknown and changing amounts of elements unseen by the analyzer; air and material humidity and ambient temperature. To solve most of these problems we used the program AssayKit for elemental and molecular composition calculation based on the fundamental parameters method. The chosen configuration of the x‐ray tube illumination cone and the detector registration cone allows measurements to be made at a wide range of distances between the analyzer and material. The XRF analyzer with this program was successfully applied to chrome–iron ore analysis in Kemi mine, Finland, for quality control of outgoing production. The accuracy of analysis—standard deviation of 1.1% for chrome and 0.8% for iron in full operation—was verified by more than 300 comparisons with chemical analysis measurements. Copyright © 2005 John Wiley &amp; Sons, Ltd.

Factors affecting the inactivation of micro-organisms by intense light pulses

To determine the influence of several factors on the inactivation of micro-organisms by intense light pulses (ILP). Micro-organisms on agar media were flashed 50 times under different conditions and their inactivation measured. Micro-organisms differed in sensitivity to ILP but no pattern was observed among different groups. Several enumeration methods to quantify the effect of ILP were investigated and showed relevant differences, shading effect and photoreactivation accounted for them, the strike method yielded the most reliable results. Higher decontamination efficiencies were obtained for Petri dishes located close to the strobe and inside the illumination cone. Decontamination efficacy decreased significantly at contamination levels >6.85 log(10). After 13 successive treatments, no resistance to ILP could be demonstrated. Media warming up depended on the distance from the strobe and the number of flashes. For an industrial implementation: the position and orientation of strobes in an unit will determine the lethality, products should be flashed as soon as possible after contamination occurs, a cooling system should be used for heat-sensitive products and flashed products should be light protected. No resistant flora is expected to develop. Conclusions derived from this work will allow a better implementation of this decontamination technique at industrial level.

Oblique-incidence illumination and collection for depth-selective fluorescence spectroscopy

Optimization of device-tissue interface parameters may lead to an improvement in the efficacy of fluorescence spectroscopy for minimally invasive disease detection. Although illumination-collection geometry has been shown to have a strong influence on the spatial origin of detected fluorescence, devices that deliver and/or collect light at oblique incidence are not well understood. Simulations are performed using a Monte Carlo model of light propagation in homogeneous tissue to characterize general trends in the intensity and spatial origin of fluorescence detected by angled geometries. Specifically, the influence of illumination angle, collection angle, and illumination-collection spot separation distance are investigated for low and high attenuation tissue cases. Results indicate that oblique-incidence geometries have the potential to enhance the selective interrogation of superficial or subsurface fluorophores at user-selectable depths up to about 0.5 mm. Detected fluorescence intensity is shown to increase significantly with illumination and collection angle. Improved selectivity and signal intensity over normal-incidence geometries result from the overlap of illumination and collection cones within the tissue. Cases involving highly attenuating tissue produce a moderate reduction in the depth of signal origin. While Monte Carlo modeling indicates that oblique-incidence designs can facilitate depth-selective fluorescence spectroscopy, optimization of device performance will require application-specific consideration of optical and biological parameters.

Segmented Linear Subspaces for Illumination-Robust Face Recognition

All images of a convex Lambertian surface captured with a fixed pose under varying illumination are known to lie in a convex cone in the image space that is called the illumination cone. Since this cone model is too complex to be built in practice, researchers have attempted to approximate it with simpler models. In this paper, we propose a segmented linear subspace model to approximate the cone. Our idea of segmentation is based on the fact that the success of low dimensional linear subspace approximations of the illumination cone increases if the directions of the surface normals get close to each other. Hence, we propose to cluster the image pixels according to their surface normal directions and to approximate the cone with a linear subspace for each of these clusters separately. We perform statistical performance evaluation experiments to compare our system to other popular systems and demonstrate that the performance increase we obtain is statistically significant.