16 May 2018 Solar-blind ultraviolet object detection based on the ultraviolet and visible bispectral airborne imaging system
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Abstract
The solar-blind ultraviolet (UV) and visible (VIS) imaging system provides a valuable tool for search and rescue missions. However, due to atmospheric scattering and absorption effects, the UV images are significantly degraded, even missing the target in some frames. A framework based on a weighted mask, with three schemes suitable for various imaging conditions is proposed. Compared with traditional methods, this framework not only preserves low-intensity target regions but also highlights and tracks any suspicious target. Scheme 1 enhances the signal-to-noise ratio (SNR) by computing the accumulating weights of sequential frames, supporting temporal and average weighting means. The temporal weighting serves as a traditional recursive temporal filtering method, which has an effect similar to that of average weighting. Scheme 2 mitigates small platform drifts by introducing a Kalman filter. Scheme 3 mitigates large platform perturbations by eliminating interference from a moving background, which is achieved by determining the warping relationship from adjacent VIS frames. The experiments are designed to cover as many situations as possible, including low-SNR imaging on a static platform, high-SNR imaging on a flat-flying small drone, and strong/weak complex target imaging on a hovering platform. The experiments assess the proposed methods and validate their predicted performance.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Chunxiao Zhang, Chunxiao Zhang, Chongbin Xu, Chongbin Xu, Gaojin Wen, Gaojin Wen, Yuanfeng Lian, Yuanfeng Lian, "Solar-blind ultraviolet object detection based on the ultraviolet and visible bispectral airborne imaging system," Optical Engineering 57(5), 053109 (16 May 2018). https://doi.org/10.1117/1.OE.57.5.053109 . Submission: Received: 21 November 2017; Accepted: 2 May 2018
Received: 21 November 2017; Accepted: 2 May 2018; Published: 16 May 2018
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