Section: Bilateral Contracts and Grants with Industry

Bilateral Contracts with Industry

Contract with Astrium on compression of satellite images

Participants : Jeremy Aghaei Mazaheri, Christine Guillemot, Claude Labit.

• Title  : Compression of satellite images.

• Research axis : §  6.3.2 .

• Partners : Astrium, Inria-Rennes.

• Funding : Astrium.

• Period : Oct.11-Sept.14.

This contract with Astrium addresses the problem of sparse representation and dictionary learning for efficient sparse coding of video signals captured from a geostationary satellite. The goal is to develop a compact spatio-temporal representation taking advantage of the high redundancy present in the video which is of very high resolution and characterized by low motion. Different methods for learning tree-structured dictionaries have been studied. The tree-structured dictionaries are well-tailored to the characteristics of the signals to be processed at each iteration of the greedy matching pursuit algorithms, while allowing efficient encoding of the produced sparse vectors. Adaptive tree-structures have been developed and the use of such dictionaries in HEVC-based intra coding has been investigated. First tests have also been carried out to known to which extent the learned dictionnaries can allow detecting the modulation transfer function (MTF) used to characterize the quality of electro-optical imaging systems on board remote sensing satellites.