Proc. SPIE. 7300, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XX
KEYWORDS: Data modeling, Reflection, Reflectivity, Surface roughness, Bidirectional reflectance transmission function, Surface properties, High dynamic range imaging, Analytical research, System on a chip, Thermal modeling
A new standard for the measurement and analysis of optical surface properties for input to the ShipIR
model (Vaitekunas, 2002) are developed and tested using paint specimens taken from the unclassified Canadian research
vessel (CFAV Quest). The theory and equations used to convert the in-lab surface property measurements into ShipIR model
input parameters are described. The resultant data consists of two thermal model input parameters, solar absorptivity (αs) and thermal emissivity epsilon;Τ), and a series of in-band surface properties, the nominal emissivity (ε), nominal specular
reflectance (ρs), angular lobe-width (e) and a grazing-angle (b) parameter. Original sample measurements in 2004 are
supplemented with new hemispherical directional reflectance (HDR) and bi-directional reflectance distribution function
(BRDF) measurements in 2008 to track the changes in the paint specimens and expand the analysis to include additional input
parameters to ShipIR. A more rigorous treatment of the BRDF model relates the HDR and BRDF measurements to a single
surface roughness parameter (σ).
Evolutionary computation can increase the speed and accuracy of pattern recognition in multispectral images, for
example, in automatic target tracking. The first method treats the clustering process. It determines a cluster of pixels
around specified reference pixels so that the entire cluster is increasingly representative of the search object. An initial
population (of clusters) evolves into populations of new clusters, with each cluster having an assigned fitness score. This
population undergoes iterative mutation and selection. Mutation operators alter both the pixel cluster set cardinality and
composition. Several stopping criteria can be applied to terminate the evolution. An advantage of this evolutionary
cluster formulation is that the resulting cluster may have an arbitrary shape so that it most nearly fits the search pattern.
The second algorithm automates the selection of features (the
center-frequency and the bandwidth) for each population
member. For each pixel in the image and for each population member, the Mahalanobis distance to the reference set is
calculated and a decision is made whether or not this pixel belongs to a target. The sum of correct and false decisions
defines a Receiver Operating Curve, which is used to measure the fitness of a population member. Based on this fitness,
the algorithm decides which population members to use as parents for the next iteration.
The advancement of computer simulation tools for high fidelity signature modeling has led to a requirement for a better understanding of effects of light scattering from surfaces. Measurements of the Bidirectional Reflectance Distribution Function (BRDF) fully describe the angular scattering properties of materials, and these may be used in signature simulations to quantitatively characterize the optical effects of surface treatments on targets. This paper reviews the theoretical and experimental techniques for characterizing the BRDF of surfaces and examines some of the popular parameterized BRDF representations that are used in signature calculations.
Optical tagging methods have the advantage that they cannot be detected by a suspicious criminal or terrorist using a radio frequency (RF) sensitive device to scan his vehicle for the presence of an RF emitting tag. We will describe two optical tagging methods in which the presence of the tagging marks can be visually discovered only by very close observation. On the other hand, the tags can be readily recognized by a surveillance team through the use of infrared imagers, either in the longwave infrared (LWIR) or in the near infrared (NIR). The first approach uses a clear coating that has a higher thermal emissivity than the glass window to which it is applied. This coating can be viewed with a thermal imager that operates in the LWIR, with the tags appearing as bright marks on a dark background. The second method uses an NIR laser illuminator and also quarter-wave thick layers applied to the license plate of a vehicle. When viewed with a polarization-sensitive imager that operates in the NIR, these quarter-wave tags appear as bright marks on a dark background. We will show sample images of both of these optical tags, as viewed in the LWIR and NIR regions, respectively.
Hyperspectral imaging has proved to be a valuable tool for performing material based discrimination of targets in highly cluttered backgrounds. A next step for utilizing this technology is to integrate spectral and spatial discrimination algorithms for Autonomous Target Recognition (ATR) applications. This paper describes a hardware and software testbed system for performing spectral/spatial ATR and presents initial results from a field test in the Anza- Borrego desert.
Achievement of ultra-high fidelity signature modeling of targets requires a significant level of complexity for all of the components required in the rendering process. Specifically, the reflectance of the surface must be described using the bi-directional distribution function (BRDF). In addition, the spatial representation of the background must be high fidelity. A methodology and corresponding model for spectral and band rendering of targets using both isotropic and anisotropic BRDFs is presented. In addition, a set of tools will be described for generating theoretical anisotropic BRDFs and for reducing data required for a description of an anisotropic BRDF by 5 orders of magnitude. This methodology is hybrid using a spectrally measured panoramic of the background mapped to a large hemisphere. Both radiosity and ray-tracing approaches are incorporated simultaneously for a robust solution. In the thermal domain the spectral emission is also included in the solution. Rendering examples using several BRDFs will be presented.
The application of advanced low observable treatments to ground vehicles has led to a requirement for a better understanding of effects of light scattering from surfaces. Measurements of the Bidirectional Reflectance Distribution Function (BRDF) fully describe the angular scattering properties of materials, and these may be used in signature simulations to quantitatively characterize the optical effects of surface treatments on targets. This paper reviews the theoretical and experimental techniques for characterizing the BRDF of surfaces and examines some of the popular parameterized BRDF representations that are used in signature calculations.
Proc. SPIE. 3375, Targets and Backgrounds: Characterization and Representation IV
KEYWORDS: Near infrared, Data modeling, Visualization, Reflectivity, Bidirectional reflectance transmission function, Modeling and simulation, Statistical modeling, Performance modeling, Systems modeling, Process modeling
Signature prediction models have become an increasingly important tool for the ground combat vehicle designer in recent years. System designers have been successful in prototyping entire vehicles in each spectral band. With this success, focused efforts to improve the accuracy of these signature models have produced robust, validated performance for many operational conditions. One of the most recent improvement in prediction models for ground vehicle systems has been improvements in surface reflectance. Surface reflectance is central to the predicted performance of these models and range from simple to very complex. Simple surface reflectance models treats the surface as totally lambertiant has an advantage of being fast to calculate but does not take into account the specular nature which all surfaces posses. The bi-directional reflectance distribution function (BRDF) is a more complex representation which allows for a more accurate representation of surface reflectance phenomena. The input to the BRDF usually comes from a laboratory sample measured in a laboratory setting. These laboratory samples are made to be perfect so that comparisons can be made between variations in formulas for the coatings. The limitation of these inputs is that surfaces that are exposed to environments effects and normal daily use are the more representative of data we are interested in. Other effects such as the conditions under which the surface coatings are applied can cause reflectance variability as well. This paper explores the variability on real targets and compares them to laboratory samples. The implication of these variations to signature models will be explored.
The application of analytical light scattering techniques for virtual prototyping the optical performance of paint coatings provides an effective tool for optimizing paint design for specific optical requirements. This paper describes the phenomenological basis for the scattering coatings computer aided design (ScatCad) code. The ScatCad code predicts the bidirectional reflectance distribution function (BRDF) and the hemispherical directional reflectance (HDR) of pigmented paint coatings for the purpose of coating design optimization. The code uses techniques for computing the pigment single scattering phase function, multiple scattering radiative transfer, and rough surface scattering to calculate the BRDF and HDR based on the fundamental optical properties of the pigment(s) and binder, pigment number density and size distribution, and surface roughness of the binder-interface and substrate. This is a significant enhancement to the two- flux, Kubelka-Munk analysis that has traditionally been used in the coatings industry. Example calculations and comparison with measurements are also presented.
Improvements in the fidelity of predictive computer models have brought requirements for more robust reflectance modeling. These requirements have focused new interest in measurement processes and data representation. Representation of the data is of critical importance to rendering models such as ray tracers and radiance renders. In these cases concise and accurate reflectance representation drives speed performance of the modeling. Many types of reflectance representations exist but the bidirectional reflectance is the most general case, from which all the others can be derived. This paper explores the bidirectional reflectance function, its measurement techniques and linkages into predictive modeling. Limitations to each of these areas will also be discussed.
Recent improvements in 'surface engineering' have helped to increase one-sun silicon solar cell efficiencies to more than 24% for float-zone grown single-crystal silicon. Texturing of the cell surface, to enhance the light coupling into cell, constitutes a significant part of this dramatic progress. Most single-crystal silicon substrates with a (100) surface orientation can be textured with relative ease using a selective or anisotropic chemical etching method. Other silicon materials, like ribbon-grown, (111) dendritic web and polycrystalline substrates do not lend themselves to chemical material removal without elaborate micro- lithographic masking method. This paper investigates the feasibility of using excimer micromachining as an alternative method of texturing silicon solar cells in general. Experiments are conducted with (111) float-zone and dendritic web-grown substrates. Using a 'diamond' patterned mask and a Kr2 excimer laser, contiguous arrays of V- shaped micro-grooves are formed on each substrate. The resulting surface texture is examined by surface profilometry and the results are correlated to the original surface micro characteristics of the samples. Sample carrier lifetimes and solar reflectances are measured prior to- and after the laser processing. The results verify the technical feasibility of excimer micro machining of (111) float zone and dendritic web single crystal substrates.
A new era in signature simulation has arrived with the development of a family of instruments for the measurement of optical properties of materials. These new instruments, covering the spectral range from 0.2 to 200 microns plus millimeter waves, have been mated with workstations which control the measurement processes, and on which software for data analysis, signature simulation, and coatings design reside. Portability of the instruments allows measurements and analysis in the laboratory, or in the field. For the first time an analyst can affordably make rapid measurements of such quantities as bi-directional or directional reflectance/emittance of sample materials, analyze, plot, and archive the measurements, and then immediately use the new measurements in a signature simulation of targets, backgrounds and scenes. Alternatively, the analyst can design a unique coating and immediately subject the design to iterative analysis for target signature control or deception. This paper discusses the instruments and techniques for accomplishing the measurements and analysis.
Commonly used methods of developing paints and evaluating their performance involve calculating the signatures of vehicles and backgrounds, this requires experimental determination of the directional and bidirectional reflectance of the surfaces involved. This paper describes the measurements required, the instruments used to make such measurements, and computer codes and techniques used for paint development and signature evaluation. Examples of bidirectional reflectance data obtained using full experimental mapping are presented. Applications of BRDF data in IR paint development are demonstrated with emphasis on validation and confirmation of computer modeling codes. Calculations of signatures using BRDF data are given using bidirectional reflectance data for two different coatings.