Ground-Based Hyperspectral Image Surveillance Systems for Explosive Detection: Part I-State of the Art and Challenges


Koz A.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, cilt.12, ss.4746-4753, 2019 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 12 Konu: 12
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1109/jstars.2019.2957484
  • Dergi Adı: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
  • Sayfa Sayıları: ss.4746-4753

Özet

Existing ground-based hyperspectral imaging (HSI) systems provide a good potential for standoff detection of explosives and their traces. The current technology, however, has still essential challenges to achieve a generic surveillance system for dynamic scenes with moving vehicles. In this regard, part I of this two-part article presents a state-of-the-art of existing HSI systems for explosive detection and discusses the future challenges for such a surveillance system. Considering the utilization of a light source and the operating spectral region, the presented overview classifies the related HSI systems as active and passive systems in the long-wave and short-wave infrared spectra, and investigates the methods in each class with respect to the targeted explosives, illumination and capturing devices, target detection algorithms, and performance evaluation methodologies. The investigation has revealed the major challenges for a generic surveillance system as 1) a thorough experimental performance validation with respect to time, date, and orientation, 2) sufficient acquisition speeds to capture moving vehicles, 3) registration and regulation of different spectral bands captured at different positions of the movement in a dynamic scene, 4) lower false positive rates required for the dynamic scenes compared to static control points, and 5) white reference compensations for the reflectance conversion in a continuous and secure surveillance system. The companion part II article then provides different solutions for reflection conversion to eliminate the dependencies to the white references for an economic and sustainable system.