Sun-glint false alarm mitigation in a maritime scenario

Alessandro Rossi; Aldo Riccobono; Stefano Landini

doi:10.1117/12.2067325

Abstract

Airborne hyperspectral imaging can be exploited to detect anomalous objects in the maritime scenario. Due to the objects high contrast with respect to the sea surface, detection can be easily accomplished by means of local anomaly detectors, such as the well-known Reed-Xiaoli (RX) algorithm. During the development of a real-time system for the detection of anomalous pixels, it has been noticed that the performance of detection is deeply affected by the presence of sun-glint. The reflection on the sea surface of the solar radiation produces a high density of alarms, that makes challenging the task of detecting the objects of interest. In this paper, it is introduced a strategy aimed at discriminating the sun-glint false alarms from the effective alarms related to targets of potential interest. False alarms due to glint are mitigated performing a local spatio-spectral analysis on each alarm furnished by the anomaly detector. The technique has been tested on hyperspectral images collected during a measurement campaign carried out near Pisa, Italy. The Selex ES SIMGA hyperspectral sensor was mounted on board of an airplane to collect high spectral resolution images in both the VNIR and SWIR spectral channels. Several experiments were carried out, setting up scenarios with small man-made objects deployed on the sea surface, so as to simulate search and rescue operations. The results have highlighted the effectiveness of the proposed solution in terms of mitigation of false alarms due to sun-glints on the maritime scenario.

Citation Download Citation

Alessandro Rossi, Alessandro Rossi, Aldo Riccobono, Aldo Riccobono, Stefano Landini, Stefano Landini, } "Sun-glint false alarm mitigation in a maritime scenario", Proc. SPIE 9250, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing II, 92500X (13 October 2014); doi: 10.1117/12.2067325; https://doi.org/10.1117/12.2067325

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