Abstract
Infrared detectors suffer from severe non-uniform noise which highly reduces image resolution and point target signal-to-noise ratio. This is the restriction for airborne point target detection systems in reaching the background limit. The existing methods are either not accurate enough, or too complex to be applied to engineering. To improve the precision and reduce the algorithm complexity of scene-based Non-Uniformity Correction (NUC) for an airborne point target detection system, a Median-Ratio Scene-based NUC (MRSBNUC) method is proposed. The method is based on the assumption that the median value of neighboring pixels is approximately constant. The NUC coefficients are calculated recursively by selecting the median ratio of adjacent pixels. Several experiments were designed and conducted. For both the clear sky scene and scene with clouds, the non-uniformity is effectively reduced. Furthermore, targets were detected in outfield experiments. For Target 1 48.36 km away and Target 2 50.53 km away, employing MRSBNUC the SNR of the target increased 2.09 and 1.73 times respectively compared to Two-Point NUC. It was concluded that the MRSBNUC method can reduce the non-uniformity of the detector effectively which leads to a longer detection distance and fewer false alarms of the airborne point target detection system.
Highlights
Airborne infrared small target detection systems are widely used in military fields for they possess night vision and anti-hidden capability, as well as mist-penetrating power
The imaging equipment is installed on various unmanned aerial vehicles (UAV) or manned aircraft
The existence of bad points will cause fixed white and black points to appear when imaging with an infrared focal plane array, which will seriously affect the visual effect of the image
Summary
Airborne infrared small target detection systems are widely used in military fields for they possess night vision and anti-hidden capability, as well as mist-penetrating power. Targets need to be detected as far away as possible for early warning. The complex aerial imaging environment seriously affects imaging quality and reduces detection rate. Infrared radiation is affected by atmospheric attenuation, such as the absorption of atmospheric gas molecules, the scattering of suspended particles in the atmosphere, and the blocking effect under meteorological conditions. Both the target and the detection system are exposed to the air, the weather, season, day and night, and clouds all affecting imaging quality.
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