25 October 2016 Hyperspectral imaging simulation of object under sea-sky background
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Proceedings Volume 10156, Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology; 101561N (2016) https://doi.org/10.1117/12.2247241
Event: International Symposium on Optoelectronic Technology and Application 2016, 2016, Beijing, China
Abstract
Remote sensing image simulation plays an important role in spaceborne/airborne load demonstration and algorithm development. Hyperspectral imaging is valuable in marine monitoring, search and rescue. On the demand of spectral imaging of objects under the complex sea scene, physics based simulation method of spectral image of object under sea scene is proposed. On the development of an imaging simulation model considering object, background, atmosphere conditions, sensor, it is able to examine the influence of wind speed, atmosphere conditions and other environment factors change on spectral image quality under complex sea scene. Firstly, the sea scattering model is established based on the Philips sea spectral model, the rough surface scattering theory and the water volume scattering characteristics. The measured bi directional reflectance distribution function (BRDF) data of objects is fit to the statistical model. MODTRAN software is used to obtain solar illumination on the sea, sky brightness, the atmosphere transmittance from sea to sensor and atmosphere backscattered radiance, and Monte Carlo ray tracing method is used to calculate the sea surface object composite scattering and spectral image. Finally, the object spectrum is acquired by the space transformation, radiation degradation and adding the noise. The model connects the spectrum image with the environmental parameters, the object parameters, and the sensor parameters, which provide a tool for the load demonstration and algorithm development.
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Biao Wang, Jia-xuan Lin, Wei Gao, Hui Yue, "Hyperspectral imaging simulation of object under sea-sky background", Proc. SPIE 10156, Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology, 101561N (25 October 2016); doi: 10.1117/12.2247241; https://doi.org/10.1117/12.2247241
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