In this paper the performance of passive range measurement imaging using stereo technique in real time applications is
described. Stereo vision uses multiple images to get depth resolution in a similar way as Synthetic Aperture Radar (SAR)
uses multiple measurements to obtain better spatial resolution.
This technique has been used in photogrammetry for a long time but it will be shown that it is now possible to do the
calculations, with carefully designed image processing algorithms, in e.g. a PC in real time.
In order to get high resolution and quantitative data in the stereo estimation a mathematical camera model is used. The
parameters to the camera model are settled in a calibration rig or in the case of a moving camera the scene itself can be
used for calibration of most of the parameters. After calibration an ordinary TV camera has an angular resolution like a
theodolite, but to a much lower price.
The paper will present results from high resolution 3D imagery from air to ground. The 3D-results from stereo
calculation of image pairs are stitched together into a large database to form a 3D-model of the area covered.
Methods for scene-based removal of fixed pattern noise from IR image sequences are described and evaluated in this paper. In particular, methods that are based on registration of global motion between individual image frames are discussed. A pre-processing calibration procedure is also presented, which produces an initial set of correction parameters. The algorithms are tested with good results on real image data from a two-dimensional focal plane array detector and a scanning one-dimensional detector.
Modern imaging systems are highly sensitive in a large dynamic range, which can give images consisting of many signal levels. Presentation of such images with varying dynamic ranges on a display with a fixed number of greylevels is difficult without losing important visual information. This paper presents several algorithms for automatic dynamic range adaptation for images. All of the algorithms are suitable for and also implemented in realtime applications. They fall mainly into two categories: histogram modification techniques and frequency based techniques. Some of the algorithms are evaluated in a perception experiment, where the goal is to get the visually most attractive images, and the experiment shows that the frequency based techniques are superior to the histogram modification techniques. Some of the proposed algorithms have proven to give visually attractive images, where none or almost none of the important information is lost, for a large selection of images with varying dynamic ranges.
KEYWORDS: Sensors, Infrared search and track, Signal processing, Image processing, Target detection, Infrared sensors, Forward looking infrared, Control systems, Signal to noise ratio, Computer simulations
Saab Bofors Dynamics has developed an IRST-system (Infra Red Search and Track) named IR-OTIS (Optical Tracking and Identification System) and flight trials have been carried out with the system mounted on a Saab JA37 Viggen fighter aircraft. This paper consists of three major parts. First an overview of Saab's IRST-programs. The second part describes the system ( IR-OTIS(Viggen) ) that made flight trials during 1998 and 1999 and finally a report from the flight trials.
IR-OTIS has mainly three operating modes:
1) IRST-mode where the system covers several different FOS (Field Of Search).
2) FLIR-mode (Forward Looking IR) where the systems LOS (Line Of Sight) is directed from the aircraft.
3) Track-mode where the built-in-tracker controls the LOS.
It is also possible to switch from IRST-mode to track-mode automatically.
Physically the IR-OTIS(Viggen) consists of the SU (Sensor Unit) and the SPU (Signal Processing Unit).
The SU is operating in the longwave IR-band with a 288*4 detector. In all modes the Sensor Unit generates images in 25 Hz and it is also possible to choose one of three FOV.
The SPU consists of a Saab designed image processing hardware and several DSPs. Functions in the SPU includes a scene-based NUC (Non Uniformity Correction), anti-Narcissus, a point-target detector including estimation of SNR and a clutter classifier for CFAR, target association, a correlation target tracker and an AGC for image presentation.
We carried out over 50 flight trials during 1998 and 1999 in three different rounds. The functionality of the system has increased during the rounds and at the end of the trials all major goals were achieved.
In this paper we present two methods for increasing the spatial resolution of images using image sequences where all frames contain the same static scene with unknown shifts. Because of the subpixel shifts, aliased frequencies appear in a slightly different way in all images, making it possibly to reconstruct frequencies above the Nyqvist frequency, thus improving the resolution. To this end, we estimate parameters in the affine transform relating the images to each other from the sequence. To show the applicability of the algorithms, many experiments have been carried out mainly using image sequences captured by a TV-camera and not only using synthetic image sequences. The results from one TV-camera sequence are presented in this report. Measurements of PSF and MTF have been carried out and the results show that we can increase the spatial resolution by almost a factor of two. This technique can be used for target identification/recognition as well as for visualization. The second method (interpolation) is possible to implement in real time.
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