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

Koz, Alper
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.


Ground-Based Hyperspectral Image Surveillance Systems for Explosive Detection: Part II-Radiance to Reflectance Conversions
Koz, Alper (Institute of Electrical and Electronics Engineers (IEEE), 2019-12-01)
The usage of white references for reflectance conversion in a captured scene for potential ground-based hyperspectral image surveillance systems suffers from security, as it exposes the location of the system, and could be expensive for a broad application due to the high prices of standard Spectralons. In Part I of this two-part article, the state-of-the-art of ground-based hyperspectral imaging systems for explosive trace detection was discussed along with the future challenges for generic surveillance sy...
Image Chain Simulation for Earth Observation Satellites
Alici, Kamil B.; Öktem, Sevinç Figen; Karci, Ozgur; Yilmaz, A. Serdar; Selimoglu, Ozgur (Institute of Electrical and Electronics Engineers (IEEE), 2019-10-01)
We present a general-purpose end-to-end image chain simulation (ICS) that enables to assess the image quality of a satellite imager for Earth observations. The image chain consists of four main components: radiometry, atmosphere, optics, and detector. In particular, ICS first computes the input radiance from the reflectance values of a high-resolution input, and then calculates the image radiance by using the optical transfer function (OTF) of the overall system. This OTF contains all the distortion effects...
Airborne laser scanning data for snow covered biomass estimation
Vazirabad, Yashar Fallah; Karslıoğlu, Mahmut Onur (SPIE-Intl Soc Optical Eng, 2009-04-13)
Airborne laser scanning provides reliable terrain data in terms of 3D coordinates. High resolutions Digital Terrain Models (DTM) are in use for many applications, including change detection of surfaces. Also the estimation of the snow depth by making use of Airborne Laser Scanning (ALS) data acquired in summer and winter is a subject of current investigations. However estimating snow depth seems problematic in vegetation covered areas. This work focuses on the investigation of the snow depth estimation usin...
Local Primitive Pattern for the Classification of SAR Images
AYTEKİN, orsan; KOÇ, mehmet; Ulusoy, İlkay (Institute of Electrical and Electronics Engineers (IEEE), 2013-04-01)
This paper proposes a new method for the classification of synthetic aperture radar (SAR) images based on a novel feature vector. The method aims at combining the intensity information of pixels with spatial information and structural relationships. Unlike classical approaches which define a static neighborhood via a rectangular moving window of predefined size and relate spatial information for each center pixel to all the pixels within that window, the local primitives (LPs) proposed in this study provide...
Field-based sub-boundary extraction from remote sensing imagery using perceptual grouping
TÜRKER, MUSTAFA; Kok, Emre Hamit (Elsevier BV, 2013-05-01)
This study presents an approach for the automatic extraction of dynamic sub-boundaries within existing agricultural fields from remote sensing imagery using perceptual grouping. We define sub-boundaries as boundaries, where a change in crop type takes a place within the fixed geometry of an agricultural field. To perform field-based processing and analysis operations, the field boundary data and satellite imagery are integrated. The edge pixels are detected using the Canny edge detector. The edge pixels are...
Citation Formats
A. Koz, “Ground-Based Hyperspectral Image Surveillance Systems for Explosive Detection: Part I-State of the Art and Challenges,” IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, pp. 4746–4753, 2019, Accessed: 00, 2020. [Online]. Available: