Laser speckle patterns typically occur when a laser beam with a narrow spectral linewidth is reflected by small-scale rough surfaces. These intensity patterns are of great interest for active imaging techniques such as gated-viewing, optical coherence tomography, or any other measurement techniques involving laser illumination. In addition to turbulence effects, surface roughness elevation plays an important role in this process. This paper presents the 2D simulation of isotropic small-scale rough surfaces with the corresponding objective speckle patterns, caused only by the reflection of laser light by those surfaces. In addition, laser speckles generated from sea surfaces, whose structures are anisotropic due to the effect of wind, are also shown. The numerical procedure for the simulation of the (material/sea) surface roughness is based on Fast Fourier Transform (FFT). Our method can simulate surfaces with given power spectral density or auto-covariance function (ACF). The most common are the Gaussian and exponential ACF’s. Thereby, the root-mean-square (rms) of surface heights and the correlation length are the main roughness descriptors for surfaces. A surface realization, using a fractal power-law for the spectral density, is also shown. For the simulation of the sea surface roughness, the main input parameters for the wave power spectrum are wind speed, wind direction and fetch. The simulation of the speckle patterns comprises the free-space propagation of a Gaussian-shaped laser beam in forward direction, the subsequent reflection at the rough surface, which introduces fluctuations in the wave phase, and the backward propagation of the reflected laser beam. The method is similar to that of the laser beam propagation in a turbulent atmosphere that uses a 2D spatial field of phase fluctuations (phase screens), whereas here, only a single 2D phase screen is considered that defines the reflective medium.
The knowledge of the optical contrast of an oil layer on the sea under various surface roughness conditions is of great interest for oil slick monitoring techniques. This paper presents a 3D simulation of a dynamic sea surface contaminated by a floating oil film. The simulation considers the damping influence of oil on the ocean waves and its physical properties. It calculates the radiance contrast of the sea surface polluted by the oil film in relation to a clean sea surface for the SWIR spectral band. Our computer simulation combines the 3D simulation of a maritime scene (open clear sea/clear sky) with an oil film at the sea surface. The basic geometry of a clean sea surface is modeled by a composition of smooth wind driven gravity waves. Oil on the sea surface attenuates the capillary and short gravity waves modulating the wave power density spectrum of these waves. The radiance of the maritime scene is calculated in the SWIR spectral band with the emitted sea surface radiance and the specularly reflected sky radiance as components. Wave hiding and shadowing, especially occurring at low viewing angles, are considered. The specular reflection of the sky radiance at the clean sea surface is modeled by an analytical statistical bidirectional reflectance distribution function (BRDF) of the sea surface. For oil at the sea surface, a specific BRDF is used influenced by the reduced surface roughness, i.e., the modulated wave density spectrum. The radiance contrast of an oil film in relation to the clean sea surface is calculated for different viewing angles, wind speeds, and oil types characterized by their specific physical properties.
A 3D simulation of the dynamic sea surface populated with whitecaps is presented. The simulation considers the
dynamic evolution of whitecaps depending on wind speed and fetch. It is suitable for imaging simulations of maritime
scenarios. The calculation of whitecap radiance is done in the SWIR spectral band by considering wave hiding and
shadowing, especially occurring at low viewing angles.
Our computer simulation combines the 3D simulation of a maritime scene (open sea/clear sky) considering whitecaps
with the simulation of light from a light source (e.g. laser light) reflected at the sea surface. The basic sea surface
geometry is modeled by a composition of smooth wind driven gravity waves. The whitecap generation is deduced from
the vertical acceleration of the sea surface, i.e. from the second moment of the wave power density spectrum. To predict
the view of a camera, the sea surface radiance must be calculated for the specific waveband with the emitted sea surface
radiance and the specularly reflected sky radiance as components. The radiances of light specularly reflected at the windroughened
sea surface without whitecaps are modeled by considering an analytical statistical sea surface BRDF
(bidirectional reflectance distribution function). A specific BRDF of whitecaps is used by taking into account their
shadowing function. The simulation model is suitable for the pre-calculation of the reflected radiance of a light source
for near horizontal incident angles where slope-shadowing of waves has to be considered.
The whitecap coverage is determined from the simulated image sequences for different wind speeds and is compared
with whitecap coverage functions from literature. A SWIR-image of the water surface of a lake populated with
whitecaps is compared with the corresponding simulated image. Additionally, the impact of whitecaps on the radiation
balance for a bistatic configuration of light source and receiver is calculated for different wind speeds.
A 3-D simulation of the polarization-dependent reflection of a Gaussian shaped laser beam on the dynamic sea surface is presented. The simulation considers polarized or unpolarized laser sources and calculates the polarization states upon reflection at the sea surface. It is suitable for the radiance calculation of the scene in different spectral wavebands (e.g. near-infrared, SWIR, etc.) not including the camera degradations. The simulation also considers a bistatic configuration of laser source and receiver as well as different atmospheric conditions. In the SWIR, the detected total power of reflected laser light is compared with data collected in a field trial. Our computer simulation combines the 3-D simulation of a maritime scene (open sea/clear sky) with the simulation of polarized or unpolarized laser light reflected at the sea surface. The basic sea surface geometry is modeled by a composition of smooth wind driven gravity waves. To predict the input of a camera equipped with a linear polarizer, the polarized sea surface radiance must be calculated for the specific waveband. The s- and p-polarization states are calculated for the emitted sea surface radiance and the specularly reflected sky radiance to determine the total polarized sea surface radiance of each component. The states of polarization and the radiance of laser light specularly reflected at the wind-roughened sea surface are calculated by considering the s- and p- components of the electric field of laser light with respect to the specular plane of incidence. This is done by using the formalism of their coherence matrices according to E. Wolf [1]. Additionally, an analytical statistical sea surface BRDF (bidirectional reflectance distribution function) is considered for the reflection of laser light radiances. Validation of the simulation results is required to ensure model credibility and applicability to maritime laser applications. For validation purposes, field measurement data (images and meteorological data) was analyzed. An infrared laser, with or without a mounted polarizer, produced laser beam reflection at the water surface and images were recorded by a camera equipped with a polarizer with horizontal or vertical alignment. The validation is done by numerical comparison of measured total laser power extracted from recorded images with the corresponding simulation results. The results of the comparison are presented for different incident (zenith/azimuth) angles of the laser beam and different alignment for the laser polarizers (vertical/horizontal/without) and the camera (vertical/horizontal).
A 3D simulation of the reflection of a Gaussian shaped laser beam on the dynamic sea surface is presented. The simulation is suitable for the pre-calculation of images for cameras operating in different spectral wavebands (visible, short wave infrared) for a bistatic configuration of laser source and receiver for different atmospheric conditions. In the visible waveband the calculated detected total power of reflected laser light from a 660nm laser source is compared with data collected in a field trial. Our computer simulation comprises the 3D simulation of a maritime scene (open sea/clear sky) and the simulation of laser beam reflected at the sea surface. The basic sea surface geometry is modeled by a composition of smooth wind driven gravity waves. To predict the view of a camera the sea surface radiance must be calculated for the specific waveband. Additionally, the radiances of laser light specularly reflected at the wind-roughened sea surface are modeled considering an analytical statistical sea surface BRDF (bidirectional reflectance distribution function). Validation of simulation results is prerequisite before applying the computer simulation to maritime laser applications. For validation purposes data (images and meteorological data) were selected from field measurements, using a 660nm cw-laser diode to produce laser beam reflection at the water surface and recording images by a TV camera. The validation is done by numerical comparison of measured total laser power extracted from recorded images with the corresponding simulation results. The results of the comparison are presented for different incident (zenith/azimuth) angles of the laser beam.
A 3D simulation of the reflection of a Gaussian shaped laser beam on the dynamic sea surface is presented. The
simulation is suitable for both the calculation of images of SWIR (short wave infrared) imaging sensor and for
determination of total detected power of reflected laser light for a bistatic configuration of laser source and receiver at
different atmospheric conditions.
Our computer simulation comprises the 3D simulation of a maritime scene (open sea/clear sky) and the simulation of
laser light reflected at the sea surface. The basic sea surface geometry is modeled by a composition of smooth wind
driven gravity waves. The propagation model for water waves is applied for sea surface animation. To predict the view
of a camera in the spectral band SWIR the sea surface radiance must be calculated. This is done by considering the
emitted sea surface radiance and the reflected sky radiance, calculated by MODTRAN. Additionally, the radiances of
laser light specularly reflected at the wind-roughened sea surface are modeled in the SWIR band considering an
analytical statistical sea surface BRDF (bidirectional reflectance distribution function). This BRDF model considers the
statistical slope statistics of waves and accounts for slope-shadowing of waves that especially occurs at flat incident
angles of the laser beam and near horizontal detection angles of reflected irradiance at rough seas.
Simulation results are presented showing the variation of the detected laser power dependent on the geometric
configuration of laser, sensor and wind characteristics.
System assessment by image simulation requires synthetic scenarios that can be viewed by the device to be simulated. In
addition to physical modeling of the camera, a reliable modeling of scene elements is necessary. Software products for
modeling of target data in the IR should be capable of (i) predicting surface temperatures of scene elements over a long
period of time and (ii) computing sensor views of the scenario.
For such applications, FGAN-FOM acquired the software products RadTherm-IR (ThermoAnalytics Inc., Calumet,
USA) and IR-Workbench (OKTAL-SE, Toulouse, France). Inspection of the accuracy of simulation results by validation
is necessary before using these products for applications. In the first step of validation, the performance of both "thermal
solvers" was determined through comparison of the computed diurnal surface temperatures of a simple object with the
corresponding values from measurements. CUBI is a rather simple geometric object with well known material parameters
which makes it suitable for testing and validating object models in IR. It was used in this study as a test body. Comparison
of calculated and measured surface temperature values will be presented, together with the results from the
FGAN-FOM thermal object code F-TOM. In the second validation step, radiances of the simulated sensor views computed
by RadTherm-IR and IR-Workbench will be compared with radiances retrieved from the recorded sensor images
taken by the sensor that was simulated.
Strengths and weaknesses of the models RadTherm-IR, IR-Workbench and F-TOM will be discussed.
CUBI is a rather simple geometrical object used in outdoor experiments with the objective of gathering data which can
be utilized in testing and validating object models in the thermal infrared. Since its introduction several years ago, CUBI
is gaining interest by an increasing number of research laboratories which are engaged in thermal infrared modelling.
Being a member of the worldwide CUBI Forum, the FGAN-FOM has installed a CUBI about 1 year ago. Since then,
CUBI surface temperatures are being recorded continuously, together with a set of associated environmental data. The
data collected are utilized to explore the capabilities of the FOM Thermal Object code F-TOM. For this purpose, the
model was modified to represent CUBI in model space. Likewise, the well-known IR signature prediction model
RadTherm/IR was applied to the CUBI problem. In this paper we will present CUBI and the philosophy behind it, the
comprehensive CUBI data collection effort at our place, and the development of the two different thermal models. Experimental
data and model predictions will be shown and compared. Strengths and weaknesses of the models will be
discussed.
A physics based 3D simulation of sea surfaces is presented. The simulation is suitable for the pre-calculation of detector images for an IR camera. Synthetic views of a maritime scenario are calculated in the MWIR and LWIR spectral bands and the images are compared with data collected in a field trial.
In our computer simulation the basic sea surface geometry is modeled by a composition of smooth wind driven gravity waves. Sea surface animation is introduced by time dependent control of the basic statistics. Choppy waves are included into the model to improve the realism of the rough sea. To predict the view of a thermal camera the sea surface radiance must be calculated. This is done with respect to the emitted sea surface radiance and the reflected sky radiance, using either MODTRAN or a semi-empirical model. Slope-shadowing of the sea surface waves is considered, which strongly influences the IR appearance of the sea surface near the horizon. MWIR and LWIR simulations are shown of sun glint as well as of whitecaps which depend upon wind velocity.
For validation purposes appropriate data sets (images and meteorological data) were selected from field measurements. A simple maritime scenario including a floating foreground object has been prepared and views of two different thermal imagers, similar to those used in the field trials, have been simulated. The validation is done by visual inspection of measured and simulated images and in addition by numerical comparison based on image statistics. The results of the comparison are presented. For an accurate reflectance calculation it is necessary to consider the maritime sky. The model is improved by inclusion of a static two-dimensional cloud layer. The cloud distribution adjusted to measured data with respect, e.g. to power spectral density and temperature distribution.
Present systems simulate sea surfaces either in the visible or in the IR band. A physics based 3D simulation of sea surfaces for the calculation of images for multiband cameras is presented here. Dynamic sea surfaces, composed of smooth wind-driven gravity waves, are generated by means of time dependent statistical models. In addition, choppy waves are modeled to improve the realism of the rough sea. The appearance of the sea in the visible and thermal bands is modeled. Sea surface radiance in the IR band is calculated with respect to the reflected sky radiance and the emitted sea surface radiance. Sun glint simulations in the visible and IR are presented. Polarization effects were incorporated to enhance the physical realism. As an example for an application a real-time animation of a sea surface with floating foreground objects is shown. The simulated images of the sea surface are in good accordance with real images.
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