Ground-Based Hyperspectral Image Surveillance Systems for Explosive Detection: Part II-Radiance to Reflectance Conversions

Date

2019-12-01

Author

Koz, Alper

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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 systems. The part II of the article proposes different approaches for reflection conversion to compensate the usage of white references at every capturing instant during surveillance, which is one of the main challenges of these systems. As an initial approach, recording the radiance of white reference only at the initialization of the system is tested by capturing an experimental setup in different days and times throughout a duration of two months. The correlations between the incident lights obtained from white references at different times, days, and orientations are compared. The effects of using a prerecorded white radiance for the reflectance conversion in the current scene are investigated. Second, a practical approach for reflectance calculation is tested by employing cheap-price reference objects having smooth characteristics in short-wave infrared spectrum, instead of expensive Spectralons. Finally, a novel reflectance conversion method is developed by using the reflectance of the static background materials in the scene rather than standard references by considering the stationary characteristics of surveillance systems. The proposed approaches are compared and verified on the baseline detection methods.

Subject Keywords

Computers in Earth Sciences, Atmospheric Science

URI

https://hdl.handle.net/11511/62335

Collections

Center for Image Analysis (OGAM), Article