The subject of this work is image coding and restoration in the context of satellite imaging. Regardless of recent developments in image restoration techniques and embedded compression algorithms, the reconstructed image still suffers from coding artifacts making its quality evaluation difficult. The objective of the thesis is to improve the quality of the final image with the study of the optimal structure of decoding and restoration regarding to the properties of the acquisition and compression processes. More essentially, the aim of this work is to propose a reliable technique to address the optimal decoding-deconvolution-denoising problem in the objective of global optimization of the compression/restoration chain. The thesis is organized in three parts. The first part is a general introduction to the problematic addressed in this work. We then review a state-of-the-art of restoration and compression techniques for satellite imaging and we describe the current imaging chain used by the French Space Agency as this is the focus of the thesis. The second part is concerned with the global optimization of the satellite imaging chain. We propose an approach to estimate the theoretical distortion of the complete chain and we present, for three different configurations of coding/restoration, an algorithm to perform its minimization. Our second contribution is also focused on the study of the global chain but is more aimed to optimize the visual quality of the final image. We present numerical methods to improve the quality of the reconstructed image and we propose a novel imaging chain based on the image quality assessment results of these techniques. The last part of the thesis introduces a satellite imaging chain based on a new sampling approach. This approach is interesting in the context of satellite imaging as it allows transferring all the difficulties to the on-ground decoder. We recall the main theoretical results of this sampling technique and we present a satellite imaging chain based on this framework. We propose an algorithm to solve the reconstruction problem and we conclude by comparing the proposed chain to the one currently used by the CNES.
