Polarimetric Scene Modeling in the Thermal Infrared
نویسندگان
چکیده
Interest in polarimetric remote sensing is gaining momentum in the visible and remains strong in the microwave regions of the spectrum. However, passive polarimetric phenomenology in the 3-14 micron infrared (IR) region is complicated by the relative contributions and complementary polarization orientation of the thermally emitted and background reflected radiance. Although this modality has found success in specific missions (i.e. surfacelaid landmine and tripwire detection), the dependence on time of day, scene conditions, scene geometry, collection geometry, etc. makes it difficult to easily perform empirical instrument design or tasking trade studies. This paper presents improvements to the modeling framework within the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model to polarimetrically render scenes in the infrared. The DIRSIG model rigorously treats the polarimetric nature of both thermally emitted and background reflected scene radiance. The correct modeling of these two components is key to accurately predicting polarized signatures for various instrument designs and collection scenarios. The DIRSIG polarized BRDF and polarized directional emissivity models are described and compared to experimentally measured data. Results showing the sensitivity of polarimetric IR phenomenology to target and background material properties, collection geometry, and scene configuration are presented.
منابع مشابه
Evaluation of the Suitability of Polarimetric Scattering and Emissivity Models with Scene Generation Software
Software based polarimetric image generation models and hardware based infrared scene projectors commonly utilize analytical forms of polarized bi-directional reflectance distribution function and emission models. Many of these models are based in first principles physical concepts, but in practice are configured as least error fits to measured signatures. The resulting analytical model may wel...
متن کاملA Hybrid Algorithm based on Deep Learning and Restricted Boltzmann Machine for Car Semantic Segmentation from Unmanned Aerial Vehicles (UAVs)-based Thermal Infrared Images
Nowadays, ground vehicle monitoring (GVM) is one of the areas of application in the intelligent traffic control system using image processing methods. In this context, the use of unmanned aerial vehicles based on thermal infrared (UAV-TIR) images is one of the optimal options for GVM due to the suitable spatial resolution, cost-effective and low volume of images. The methods that have been prop...
متن کاملPolarimetric Effects in Non-polarimetric Imaging
Radiative transfer is commonly modeled as the propagation of unpolarized radiation. More accurate approaches utilizing polarimetric quantities are usually only applied to sensors that purposefully discriminate polarimetric information. In this paper, we examine the effect on fidelity of utilizing polarimetric radiative transfer modeling for non-polarimetric sensors. We show that if the primary ...
متن کاملPolarimetric Calibration and Characterization of the Telops Field Portable Polarimetric-hyperspectral Imager in the Long Wave Infrared Thesis
Polarimetric-hyperspectral remote sensing is a promising field that brings two traditionally independent modalities together to enhance scene characterization capabilities. The Telops polarimetric-hyperspectral imager (P-HSI) combines these technologies and provides a combined imaging and spectral capability that is considered state-of-the art. The Defense Threat Reduction Agency (DTRA) funded ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007