Section: New Results

InnovationLab with I2S, sparse signals & optimisation

Participants : M. Martin, A. Zebadua, S. Sakka, N. Brodu, K. Daoudi, A. Cherif [I2S] , J. L. Vallancogne [I2S] , A. Cailly [I2S] .

During 2018 A. Zebadua was involved for the first time in the use of non-convex optimization methods and proximal operators, to solve inverse problems in image processing. Within the framework of the joint project with i2s, his main task was to work together with the research engineers to understand, implement, adapt and reduce the execution time of the algorithms developed by H. Badri in his doctoral thesis. These algorithms were developed in a scientific context, it was, therefore, necessary to adapt them to an industrial context with practical constraints.

S. Sakka has been implementating of the demosaicing algorithm to reconstruct a full-color image from raw images acquired by scanning. Colors are generated by a mask of Bayer. This algorithm uses the Hamilton Method and the Edge aware smoothing algorithm. He has been performing benchmarks for performance and quality test, and has written the technical report about the demosaicing algorithm. S. Sakka has been implementing iterative algorithms for linear system resolution useful for inpaitnig image processing algorithm.

S. Sakka has been implementating of the demosaicing algorithm to reconstruct a full-color image from raw images acquired by scanning. Colors are generated by a mask of Bayer. This algorithm uses the Hamilton Method and the Edge aware smoothing algorithm. He has been performing benchmarks for performance and quality test, and has written the technical report about the demosaicing algorithm. S. Sakka has been implementing iterative algorithms for linear system resolution useful for inpainting image processing algorithm.

C. Sakka has been participating in the GPU Technology Conference organized by Nvidia in Munich and attending the NVIDIA Deep Learning School, and A. Zebadua has been participating to the winter school itwist18 in optimization from November 19th to 20th in Marseille.

M. Martin studied and made comparison between two methods : EAS (Edge Aware Smoothing) algorithm and LRT (low rank transfer) for denoising. She has been writing technical report to choose with I2S the best method : more efficient, less time. M. Martin has also been implementing denoising in C++ with librairy opencv and gpu. She has been setting up code sharing with I2S on gitlab Inria