KEYWORDS: Speckle, Turbulence, Modulation transfer functions, Signal to noise ratio, Imaging systems, Image quality, Sensors, 3D modeling, Scintillation, 3D image reconstruction
Range-gated or burst illumination systems have recently drawn a great deal of attention concerning the use for target classification. The development of eye-safe lasers and detectors will make these systems ideal to be combined with thermal imagers for long range targeting at night but also for short range security applications. This presentation will describe performance modelling and simulation of range-gated systems and discuss these together with experimental data.
This presentation will review some of the work on range gated imaging undertaken at the Swedish Defence Research
Agency (FOI). Different kind of systems covering the visible to 1.5 μm region have been studied and image examples
from various field campaigns will be given. Example of potential applications will be discussed.
This paper presents the Swedish land mine and UXO detection project "Multi Optical Mine Detection System," MOMS, and the research carried out so far. The goal for MOMS is to provide knowledge and competence for fast detection of mines, especially surface laid mines, by the use of both active and passive optical sensors. A main activity was to collect information and gain knowledge about phenomenology; i.e. features or characteristics that can give a detectable signature or contrast between object and background, and to carry out a phenomenology assessment. A large effort has also been put into a scene description to support phenomenology assessment and provide a framework for further experimental campaigns. Also, some preliminary experimental results are presented and discussed.
In this work we evaluate the imaging performance of a range-gated underwater system in natural waters. Trials have
been performed in both turbid and clear water. The field trials show that images can be acquired at significantly longer
distances with the gated camera, compared to a conventional video camera. The distance where a target can be detected
is increased by a factor of 2. For images suitable for object identification, the range improvement factor is typically 1.5.
We also show examples of image processing of the range-gated images, which increases the image quality significantly.
In this paper, we present techniques related to registration and change detection using 3D laser radar data. First, an experimental evaluation of a number of registration techniques based on the Iterative Closest Point algorithm is presented. As an extension, an approach for removing noisy points prior to the registration process by keypoint detection is also proposed. Since the success of accurate registration is typically dependent on a satisfactorily accurate starting estimate, coarse registration is an important functionality. We address this problem by proposing an approach for coarse 2D registration, which is based on detecting vertical structures (e.g. trees) in the point sets and then finding the transformation that gives the best alignment. Furthermore, a change detection approach based on voxelization of the registered data sets is presented. The 3D space is partitioned into a cell grid and a number of features for each cell are computed. Cells for which features have changed significantly (statistical outliers) then correspond to significant changes.
Range-gated or burst illumination systems have recently drawn a great deal of attention concerning the use for target classification. The development of eye safe lasers and detectors will make these systems ideal to be combined with thermal imagers for long range targeting at night but also for short range security applications like reading of signs and licence plates, looking into cars and buildings etc. Examples of imagery collected for different range and atmospheric conditions will be presented and discussed with respect to image quality and processing techniques.
Atmospheric propagation degradation effects including attenuation, aerosol scattering and turbulence have a great
impact on the performance of optical systems. Relevant military optical systems include active and passive imaging for
target recognition, free-space optical communication and DIRCM/EOCM. This paper will report on experimental work
including measurement of retro signals at 1.5 and in the 3-5 μm wavelength regions for evaluation of retro communication
links and DIRCM performance. Imaging experiments using a range-gated system both in the active and
passive mode at 1.5 μm, will also be carried along the same paths. A dedicated target box and test targets have been
fabricated for mounting on a mast at 8 km from our laboratory. The box contains reflectors and receivers in different
slots each of which can be opened by a telephone call. A heated target on top simulates a point target in the IR region.
The test targets are aimed for the range-gated imaging system. Preliminary experimental data will be presented and
discussed.
As a part of the Swedish mine detection project MOMS, an initial field trial was conducted at the Swedish EOD and
Demining Centre (SWEDEC). The purpose was to collect data on surface-laid mines, UXO, submunitions, IED's, and
background with a variety of optical sensors, for further use in the project. Three terrain types were covered: forest,
gravel road, and an area which had recovered after total removal of all vegetation some years before. The sensors used in
the field trial included UV, VIS, and NIR sensors as well as thermal, multi-spectral, and hyper-spectral sensors, 3-D laser
radar and polarization sensors. Some of the sensors were mounted on an aerial work platform, while others were placed
on tripods on the ground. This paper describes the field trial and the presents some initial results obtained from the
subsequent analysis.
KEYWORDS: 3D image processing, Imaging systems, Sensors, 3D image reconstruction, Monte Carlo methods, Pulsed laser operation, 3D acquisition, Systems modeling, Statistical analysis, Linear filtering
An approach to long-range 3-D imaging using laser illuminated range-gated viewing is presented. The basis for 3-D scene reconstruction is an image sequence acquired using a sliding gate delay time. Two different methods are suggested, and algorithm performance is investigated through Monte Carlo simulations using a simplified system and imaging model. Assumptions are justified by comparison with real measurements at range of 0.8 to 7.2 km. It is shown that range resolution and precision become significantly better than system design parameters such as gate length, gate transition length, and gate step length. The presented reconstruction methods thus enable high-precision range imaging using available long-range gated imaging systems.
One of the more exciting capabilities foreseen for future 3-D imaging laser radars is to see through vegetation and camouflage nettings. We have used ground based and airborne scanning laser radars to collect data of various types of terrain and vegetation. On some occasions reference targets were used to collect data on reflectivity and to evaluate penetration. The data contains reflectivity and range distributions and were collected at 1.5 and 1.06 μm wavelength with range accuracies in the 1-10 cm range. The seasonal variations for different types of vegetation have been studied. A preliminary evaluation of part of the data set was recently presented at another SPIE conference. Since then the data have been analyzed in more detail with emphasis on testing algorithms and future system performance by simulation of different sensors and scenarios. Evaluation methods will be discussed and some examples of data sets will be presented.
This paper will describe measurements of snow reflection using laser radar. There seems to be a rather limited number
of publications on snow reflection related to laser radar, which is why we decided to investigate a little more details of
snow reflection including that from different kinds of snow as well as the angular reflection properties.
We will discuss reflectance information obtained by two commercial scanning laser radars using the wavelengths
0.9 μm and 1.5 μm. Data will mainly be presented at the eye safe wavelength 1.5 μm but some measurements were also
performed for the wavelength 0.9 μm. We have measured snow reflection during a part of a winter season which gave
us opportunities to investigate different types of snow and different meteorological conditions.
The reflection values tend to decrease during the first couple of hours after a snowfall. The snow structure seems to be
more important for the reflection than the snow age. In general the snow reflection at 1.5 μm is rather low and the
reflectivity values can vary between 0.5 and 10 % for oblique incidence depending on snow structure which in turn
depends on age, air temperature, humidity etc. The snow reflectivity at the 0.9 μm laser wavelength is much higher,
more than 50 % for fresh snow. Images of snow covered scenes will be shown together with reflection data including
BRDFs.
KEYWORDS: 3D acquisition, Target recognition, LIDAR, Sensors, 3D image processing, 3D modeling, Laser systems engineering, Data modeling, Imaging systems, Clouds
This paper presents our ongoing research activities on target recognition from data generated by 3-D imaging laser radar. In particular, we focus on future full flash imaging 3-D sensors. Several techniques for laser range imaging are applied for modelling and simulation of data from this kind of 3-D sensor systems. Firstly, data from an experimental gated viewing system is used. Processed data from this system is useful in assisting an operator in the target recognition task. Our recent work on target identification at long ranges, using range data from the gated viewing system, provides techniques to handle turbulence, platform motion and illumination variances from scintillation and speckle noise. Moreover, the range data is expanded into 3-D by using a gating technique that provides reconstruction of the target surface structure. This is shown at distances out to 7 km. Secondly, 3-D target data is achieved at short ranges by using different scanning laser radar systems. This provides high-resolution 3-D data from scanning a target from one single view. However, several scans from multiple viewing angles can also quite easily be merged for more detailed target representations. This is, for example, very useful for recognizing targets in vegetation. Hereby, we achieve simulated 3-D sensor data from both short and long
ranges (100 meters out to 7 km) at various spatial resolutions. Thirdly, real data from the 3-D flash imaging system by US Air Force Research Lab (AFRL/SNJM), Wright Patterson Air Force Base, has recently been made available to FOI and also used as input in the development of aided target recognition methods. High-resolution 3-D target models are used in the identification process and compared to the 3-D target data (point cloud) from the various laser radar systems. Finally, we give some examples from our work that clearly show that future 3-D laser radar systems in cooperation with signal- and image analysis techniques have a great potential in the non-cooperative target recognition task and will provide several new and interesting capabilities, for example, to reveal targets hidden in vegetation.
This paper wil give an overview of 3D laser sensing and related activities at the Swedish Defence Research Agency (FOI) in the view of system needs and applications. Our activites include data collection of laser signatures for target and backgrounds at various wavelengths. We will give examples of such measurements. The results are used in building sythetic environments, modellin of laser radar systems and as training sets for development of algorithms for target recognition and weapon applications. Present work on rapid environment assessment includes the use of data from airborne laser for terrain mapping and depth sounding. Methods for automatic target detection and object classification (buildings, trees, man-made objects etc.) have been developed together with techniques for visualisation. This will be described in more detail in a separate paper. The ability to find and correctly identify "difficult" targets, being either at very long ranges, hidden in the vegetation, behind windows or under camouflage, is one of the top priorities for any military force. Example of such work will be given using range gated imagery and 3D scanning laser radars. Different kinds of signal processing approaches have been studied and will be presented more in two separate papers. We have also developed modeling tools for both 2D and 3D laser imaging. Finally we will discuss the use of 3D laser radars in some system applications in the light of new component technology, processing needs and sensor fusion.
KEYWORDS: Stereolithography, Lithium, LIDAR, Systems modeling, Reconstruction algorithms, Detection and tracking algorithms, Imaging systems, Laser systems engineering, 3D modeling, Data modeling
Over the years imaging laser radar systems have been developed for both military and civilian (topographic) applications. Among the applications, 3D data is used for environment modeling and object reconstruction and recognition. The data processing methods are mainly developed separately for military or topographic applications, seldom both application areas are in mind. In this paper, an overview of methods from both areas is presented. First, some of the work on ground surface estimation and classification of natural objects, for example trees, is described. Once natural objects have been detected and classified, we review some of the extensive work on reconstruction and recognition of man-made objects. Primarily we address the reconstruction of buildings and recognition of vehicles. Further, some methods for evaluation of measurement systems and algorithms are described. Models of some types of laser radar systems are reviewed, based on both physical and statistical approaches, for analysis and evaluation of measurement systems and algorithms. The combination of methods for reconstruction of natural and man-made objects is also discussed. By combining methods originating from civilian and military applications, we believe that the tools to analyze a whole scene become available. In this paper we show examples where methods from both application fields are used to analyze a scene.
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