Efficient surface and subsurface land mine detection is still one of the several important tasks in the
civilian and military areas. Often information derived from multiple sensors are fused together to lead a
net gain in probability of detection of these land mines. Some drawbacks of this approach are the different
sensor output formats and the overall processing efficiency of the system. To overcome some of the
aforementioned concerns we propose a simple and efficient image fusion using logical operators. The
proposed technique uses logical operators to fuse multiple images derived from a single sensor. The
logical fusion operation is applied to the output of the sensor to lead a logically fused image. This image
serves as an input to the detection algorithm. The proposed technique is shown to improve the probability
of detection of land mines. This improvement is shown using the ROC curve approach.
KEYWORDS: Land mines, Image fusion, Sensors, Mining, Polarization, Polarimetry, General packet radio service, Detection and tracking algorithms, Infrared radiation, Electromagnetism
Detection and clearance of subsurface land mines has been one of the challenging humanitarian and
military tasks. Among the several surface land mines detection techniques available, passive polarimetric
in the visible range holds a high promise to lead a high probability of detection. In this paper we show
how a single sensor producing multiple polarized and unpolarized imagery can be used to improve the
probability of detection of subsurface land mines. This improvement is shown using the Receiver
Operation Characteristic (ROC) curve approach.
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