Optronic System Imaging Simulator (OSIS): Imager simulation tool of the ECOMOS project

ECOMOS is a multinational effort within the framework of an EDA Project Arrangement. Its aim is to provide a generally accepted and harmonized European computer model for computing nominal Target Acquisition (TA) ranges of optronic imagers operating in the Visible or thermal Infrared (IR). The project involves close co-operation of defense and security industry and public research institutes from France, Germany, Italy, The Netherlands and Sweden. ECOMOS uses two approaches to calculate Target Acquisition (TA) ranges, the analytical TRM4 model and the image-based Triangle Orientation Discrimination model (TOD). In this paper the IR imager simulation tool, Optronic System Imaging Simulator (OSIS), is presented. It produces virtual camera imagery required by the TOD approach. Pristine imagery is degraded by various effects caused by atmospheric attenuation, optics, detector footprint, sampling, fixed pattern noise, temporal noise and digital signal processing. Resulting images might be presented to observers or could be further processed for automatic image quality calculations. For convenience OSIS incorporates camera descriptions and intermediate results provided by TRM4. For input OSIS uses pristine imagery tied with meta information about scene content, its physical dimensions, and gray level interpretation. These images represent planar targets placed at specified distances to the imager. Furthermore, OSIS is extended by a plugin functionality that enables integration of advanced digital signal processing techniques in ECOMOS such as compression, local contrast enhancement, digital turbulence mitiga- tion, to name but a few. By means of this image-based approach image degradations and image enhancements can be investigated, which goes beyond the scope of the analytical TRM4 model

Image based performance analysis of thermal imagers

Due to advances in technology, modern thermal imagers resemble sophisticated image processing systems in functionality. Advanced signal and image processing tools enclosed into the camera body extend the basic image capturing capability of thermal cameras. This happens in order to enhance the display presentation of the captured scene or specific scene details. Usually, the implemented methods are proprietary company expertise, distributed without extensive documentation. This makes the comparison of thermal imagers especially from different companies a difficult task (or at least a very time consuming/expensive task - e.g. requiring the execution of a field trial and/or an observer trial). For example, a thermal camera equipped with turbulence mitigation capability stands for such a closed system. The Fraunhofer IOSB has started to build up a system for testing thermal imagers by image based methods in the lab environment. This will extend our capability of measuring the classical IR-system parameters (e.g. MTF, MTDP, etc.) in the lab. The system is set up around the IR- scene projector, which is necessary for the thermal display (projection) of an image sequence for the IR-camera under test. The same set of thermal test sequences might be presented to every unit under test. For turbulence mitigation tests, this could be e.g. the same turbulence sequence. During system tests, gradual variation of input parameters (e. g. thermal contrast) can be applied. First ideas of test scenes selection and how to assembly an imaging suite (a set of image sequences) for the analysis of imaging thermal systems containing such black boxes in the image forming path is discussed

Simulation of oceanic whitecaps and their reflectance characteristics in the short wavelength infrared

The knowledge of the spatial energy (or power) distribution of light beams reflected at the dynamic sea surface is of great practical interest in maritime environments. For the estimation of the light energy reflected into a specific spatial direction a lot of parameters need to be taken into account. Both whitecap coverage and its optical properties have a large impact upon the calculated value. In published literature, for applications considering vertical light propagation paths, such as bathymetric lidar, the reflectance of sea surface and whitecaps are approximated by constant values. For near-horizontal light propagation paths the optical properties of the sea surface and the whitecaps must be considered in greater detail. The calculated light energy reflected into a specific direction varies statistically and depends largely on the dynamics of the wavy sea surface and the dynamics of whitecaps. A 3D simulation of the dynamic sea surface populated with whitecaps is presented. The simulation considers the evolution of whitecaps depending on wind speed and fetch. The radiance calculation of the maritime scene (open sea/clear sky) populated with whitecaps is done in the short wavelength infrared spectral band. Wave hiding and shadowing, especially occurring at low viewing angles, are considered. The specular reflection of a light beam at the sea surface in the absence of whitecaps is modeled by an analytical statistical bidirectional reflectance distribution function (BRDF) of the sea surface. For whitecaps, a specific BRDF is used by taking into account their shadowing function. To ensure the credibility of the simulation, the whitecap coverage is determined from simulated image sequences for different wind speeds and compared to whitecap coverage functions from literature. The impact of whitecaps on the radiation balance for bistatic configuration of light source and receiver is calculated for a different incident (zenith/azimuth angles) of the light beam and is presented for two different wind speeds

Simulation of laser beam reflection at the sea surface modeling and validation

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 consideri ng 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

Noise-insensitive no-reference image blur estimation by convolutional neural networks

A few image quality metrics for blur assessment have been presented in the last years. However, most of those metrics do not take image noise into account. Yet, image noise is an unavoidable part of the image forming process with digital cameras. Some thermal imagers show larger sensor noise and inhomogeneity compared to cameras operating in the visible range. Further, natural imagery might contain a combination of several degradations. Assessment of degraded images by observer trials is expensive and time consuming. A single robust quality metric might be derived by metrics highly responsive to single degradations and insensitive to others. Hence separate assessment of image blur and noise seems to be reasonable. In this paper we present a deep learning approach for noise-insensitive blur predictions by using Convolutional Neural Networks (CNN) on image patches. In contrast to current blur metrics the model output is highly correlated to blur distortion over a wide range of image noise. The model is trained on images of ImageNet database impaired by Gaussian blur and noise and tested on artificial and natural image data. Local blur estimation based on patches is especially useful for estimation of non-uniform blur due to motion and atmospheric turbulence

Workbench for the computer simulation of underwater gated viewing systems

In this paper we introduce a software tool for image based computer simulation of an underwater gated viewing system. This development is helpful as a tool for the discussion of a possible engagement of a gated viewing camera for underwater imagery. We show the modular structure of implemented input parameter sets for camera, laser and environment description and application examples of the software tool. The whole simulation includes the scene illumination through a laser pulse with its energy pulse form and length as well as the propagation of the light through the open water taking into account complex optical properties of the environment. The scene is modeled as a geometric shape with diverse reflective areas and optical surface properties submerged in the open water. The software is based on a camera model including image degradation due to diffraction, lens transmission, detector efficiency and image enhancement by digital signal processing. We will show simulation results on some example configurations. Finally we will discuss the limits of our method and give an outlook to future development