Very high resolution multispectral imaging reached a high level of reliability and accuracy for target detection and
classification. However, in an urban scene, the complexity is raised, making the detection and the identification of small
objects difficult. One way to overcome this difficulty is to combine spectral information with 3D data. A set of (very
high resolution) airborne multispectral image sequences was acquired over the urban area of Zeebrugge, Belgium. The
data consist of three bands in the visible (VIS) region, one band in the near infrared (NIR) range and two bands in the
mid-wave infrared (MWIR) region. Images are obtained images at a frame rate of 1/2 frame per second for the VIS and
NIR image and 2 frames per second for the MWIR bands. The sensors have a decimetric spatial resolution. The
combination of frame rate with flight altitude and speed results in a large overlap between successive images. The
current paper proposes a scheme to combine 3D information from along-track stereo, exploiting the overlap between
images on one hand and spectral information on the other hand for unsupervised detection of targets. For the extraction
of 3D information, the disparity map between different image pairs is determined automatically using an MRF-based
method. For the unsupervised target detection, an anomaly detection algorithm is applied. Different methods for inserting
the obtained 3D information into the target detection scheme are discussed.
This paper describes a challenge problem whose scope is detection of stationary vehicles in foliage using VHF-band SAR data. The data for this challenge problem consists of images collected by the Swedish CARABAS-II system which produces SAR images at the low VHF-band (20-90 MHz). At these frequencies the electromagnetic energy from the radar penetrates the foliage of the forest, providing a return from a target concealed in a forest. Thus, VHF-band SAR technology transforms the foliage penetration problem into a traditional detection problem where the goal is to reduce the false alarm rate (FAR). Reducing the FAR requires suppressing the clutter in a VHF-band SAR image which is dominated by larger tree trunks, buildings and other man-made objects. The purpose of releasing the CARABAS-II data set is to provide the community with VHF-band SAR data that supports development of new algorithms for robust target detection with a low false alarm rate. The set of images supports single-pass, two-pass and multi-pass target detection.
VHF-band SAR used in conjunction with change detection techniques has shown promising results for wide-area surveillance of ground targets . By using VHF-band frequencies both targets in the open as well as concealed by foliage may be detected. These detections occur with high probability and with a low false-alarm rate. VHF-band SAR is able to detect hidden targets because both foliage attenuation and clutter backscatter is small. The clutter is further repressed through the use of change detection, thus significantly reducing the false-alarm rate. Change detection techniques are well suited for VHF-band SAR since temporal decorrelation is small at these large wavelengths.
The CARABAS-II system performed a data collection during the summer of 2002. The primary goal of this collection was to gather data to evaluate VHF-band SAR change detection performance under various operating conditions. This paper reports the results obtained. In general, the results show a VHF-band SAR system employing change detection can reliably and robustly detect truck-sized targets hidden in foliage. The detection performance does deteriorate under certain conditions. A significant reduction is found for near-grazing angles. Additionally, a significant performance loss is found for smaller-sized targets when the radar bandwidth is reduced.