Abstract
Several attempts have been lately proposed to tackle the problem of recovering the original image of an underwater scene using a sequence distorted by water waves. The main drawback of the state of the art is that it heavily depends on modelling the waves, which in fact is ill-posed since the actual behavior of the waves along with the imaging process are complicated and include several noise components; therefore, their results are not satisfactory. In this chapter, we address the problem by formulating a data-driven two-stage approach, each stage is targeted towards a certain type of noise. The first stage leverages the temporal mean of the sequence to overcome the structured turbulence of the waves through an iterative registration algorithm. The result of the first stage is a better structured sequence, in which the low-rank property is uncovered, thus allowing us to employ low-rank optimization as a second stage in order to eliminate the remaining sparse noise.
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Oreifej, O., Shah, M. (2014). Seeing Through Water: Underwater Scene Reconstruction. In: Robust Subspace Estimation Using Low-Rank Optimization. The International Series in Video Computing, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-319-04184-1_3
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DOI: https://doi.org/10.1007/978-3-319-04184-1_3
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