Hyperspetracl image synthesis
8 Octobre 2021
Catégorie : Stagiaire
Internship: Hyperspectral image synthesis
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 studyand will be followed by the development of the application.
This internship involves two laboratories: FEMTO-ST department DISC and the IMVIA. Some of the laboratories research areas are on data and image analysis, digital vision and computer science.
This internship is part of the COQUIIAJ project. The project aims at the creation of a hyperspectral images hyperspectral synthetic images database for deep learning application. This project will start in September 2022 and will last 3 years. The internship may lead to a thesis.
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.
- N. 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.
- 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.
Key-words: image synthesis, hyperspectral.
Date and duration
- Duration: 5-6 months,
- Start: between February and April 2022.
IMVIA laboratory in Dijon or Le Creusot (France).