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Internship: Hyperspectral Image Synthesis

Job description

The objective is to carry out a geometric and photometric modeling of a hyperspectral camera and to implement it in an image synthesis software like blender, rhyno3D or opencascade. The work will start with a bibliographic study and will be followed by the development of the application.
The bibliography work is divided into two themes: hyper-spectral imaging and image synthesis:
• To define the image of an object, it is necessary to know several characteristics such as its reflectance, its shape, its brdf, etc. The bibliographic study will be used to extract the essential characteristics for the generation of hyperspectral images.
• The bibliographic research will also lead to the choice of the image synthesis method (ray tracing, z-buffer, etc.) and the rendering engine best suited to the problem.
Thereafter, the work of the internship will consist in implementing, in the selected software tool, the camera and object modeling (acquisition sensitivity curves, object’s spectral properties, etc.). This will allow us to obtain a set of synthetic images that will be compared to real acquisitions.

• Hoarau, Romain. Rendu interactif d’image hyper spectrale par illumination globale pour la prédiction de la signature infrarouge d’aéronefs. 2019. Thèse de doctorat. AIX-MARSEILLE UNIVERSITE.
• Scanlan, Neil W., John R. Schott, and Scott D. Brown. “Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery." Imaging Spectrometry IX. Vol. 5159. International Society for Optics and Photonics, 2004.

Required skills
• Level: Master 2 student,
• Good programming skills in python or C/C++,
• Knowledge of geometric camera modelling,
• Knowledge in colour/multispectral imaging,
• Dynamism and autonomy to integrate a multidisciplinary research team.


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