Fourier Based Pre-Processing For Seeing Through Water

Jerin Geo James, Ajit Rajwade; Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2020, pp. 109-117


Consider a scene submerged underneath a fluctuating water surface. Images of such a scene, when acquired from a camera in the air, exhibit significant spatial distortions. In this paper, we present a novel, computationally efficient pre-processing algorithm to correct a significant amount (~ 50%) of apparent distortion present in video sequences of such a scene. We demonstrate that when the partially restored video output from this stage is given as input to other methods, it significantly improves their performance. This algorithm involves (i) tracking a small number N of salient feature points across the T frames to yield point-trajectories \ \boldsymbol q_i \triangleq \ (x_ it ,y_ it )\ _ t=1 ^T\ _ i=1 ^N, and (ii) using the point-trajectories to infer the deformations at other non-tracked points in every frame. A Fourier decomposition of the N trajectories, followed by a novel Fourier phase-interpolation step, is used to infer deformations at all other points. Our method exploits the inherent spatio-temporal characteristics of the fluctuating water surface to correct non-rigid deformations to a very large extent. The source code, datasets and supplemental material can be accessed at [1], [2].

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author = {James, Jerin Geo and Rajwade, Ajit},
title = {Fourier Based Pre-Processing For Seeing Through Water},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {March},
year = {2020}