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Fast and accurate image registration. Applications to on-board satellite imaging.

Abstract : This thesis starts with an in-depth study of fast and accurate sub-pixel shift estimationmethods. A full comparison is performed based on the common shift estimation problems occurring in real-life applications, namely, varying SNR conditions, differentdisplacement magnitudes, non-preservation of the brightness constancy constraint, aliasing, and most importantly, limited computational resources. Based on this study, in collaboration with CNES (the French space agency), two problems that are crucial for the digital optics of earth-observation satellites are analyzed.We first study the wavefront correction problem in an active optics context. We propose a fast and accurate algorithm to measure the wavefront aberrations on a Shack-HartmannWavefront Sensor (SHWFS) device observing the earth. We give here a review of state-of-the-art methods for SHWFS used on extended scenes (such as the earth) and devise a new method for improving wavefront estimation, based on a carefully refined approach based on the optical flow equation. This method takes advantage of the small shifts observed in a closed-loop wavefront correction system, yielding improved accuracy using fewer computational resources. We also propose two validation methods to ensure a correct wavefront estimation on extended scenes. While the first one is based on a numerical adaptation of the (theoretical) lower bounds of image registration, the second method rapidly discards landscapes based on the gradient distribution, inferred from the Eigenvalues of the structure tensor.The second satellite-based application that we address is the numerical design of a new generation of Time Delay Integration (TDI) sensor. In this new concept, active real-time stabilization of the TDI is performed to extend considerably the integration time, and therefore to boost the images SNR. The stripes of the TDI cannot be fused directly by addition because their position is altered by microvibrations. These must be compensated in real time using limited onboard computational resources with high subpixel accuracy. We study the fundamental performance limits for this problem and propose a real-time solution that nonetheless gets close to the theoretical limits. We introduce a scheme using temporal convolution together with online noise estimation, gradient-based shift estimation and a non-conventional multiframe method for measuring global displacements. The obtained results are conclusive on the fronts of accuracy and complexity and have strongly influenced the final decisions on the future configurations of Earth observation satellites at CNES.For more complex transformation models, a new image registration method performing accurate robust model estimation through point matches between images is proposed here. The difficulty coming from the presence of outliers causes the failure of traditional regression methods. In computer vision, RANSAC is definitely the most renowned method that overcomes such difficulties. It discriminates outliers by randomly generating minimalist sampled hypotheses and verifying their consensus over the input data. However, its response is based on the single iteration that achieved the largest inlier support, while discarding all other generated hypotheses. We show here that the resulting accuracy can be improved by aggregating all hypotheses. We also propose a simple strategy that allows to rapidly average 2D transformations, leading to an almost negligible extra computational cost. We give practical applications to the estimation of projective transforms and homography+distortion transforms. By including a straightforward adaptation of the locally optimized RANSAC in our framework, the proposed approach improves over every other available state-of-the-art method. A complete analysis of the proposed approach is performed, demonstrating its improved accuracy, stability and versatility.
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Submitted on : Wednesday, March 8, 2017 - 3:48:06 PM
Last modification on : Thursday, April 15, 2021 - 3:31:36 AM
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  • HAL Id : tel-01485321, version 1



Martin Rais. Fast and accurate image registration. Applications to on-board satellite imaging.. General Mathematics [math.GM]. Université Paris Saclay (COmUE); Universitat de les Illes Balears (@Université des iles Baléares), 2016. English. ⟨NNT : 2016SACLN077⟩. ⟨tel-01485321⟩



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