With the aim to recover the planar underwater scenes from a video sequence severely distorted by water waves,a reconstruction framework which integrated robust registration with lucky image approaches was proposed.At first,an iterative robust registration algorithm was used to eliminate most geometric deformations and recover the water surface.Then the best image patches selected from the corrected video frames were stitched together.With the experimental results,it is found that,in terms of restoration accuracy,visual effects and computational efficiency,the suggested algorithm always significantly outperforms better than the method employing robust registration and sparse noise elimination,leading to state-of-the-art performance on the task of underwater image restoration from video sequences.

Underwater Image Restoration Algorithm from Distorted Video

Dorn (O) Inverse Problems and Imaging Inverse Problems are found almost everywhere nowadays not only in science and engineering, but also in finance and economy. Solving an inverse problem comes with specific challenges. Most commonly it involves theory, numerical experiments and some familiarity with specific applications. In the following, I give some examples which students might be interested in to work on. Most of them involve a component of so-called ‘forward modelling’, which essentially is numerical simulation (thereby some familiarity with a programming language such as MATLAB, C, C++, Fortran90 etc is required, or the willingness to learn basics of such a language as part of the project), which could be the focus or just a part of the project. Then also the aspect of inversion is involved, which makes use of the results of the ‘forward modelling’ in some way for data inversion. In the following, I give an ad-hoc list of possible topics. I am happy to discuss these and also additional topics brought forward to me by interested students. Notice that for some of these projects it is advisable that students also take the course module MATH46132 Numerical Optimization and Inverse Problems.

Inverse Problems and Imaging

Visual inspection is a common procedure during outages of nuclear power plants. For the underwater visual inspection of the nuclear plant reactor after fuel reloading, the water turbulence generated by nuclear fuel assemblies can seriously degrade the quality of video. Online image restoration is required in order to meet the need of minimizing the duration of visual inspection. The paper proposes a new method to solve the image degradation and to realize online image restoration when visual inspection. First, the image degradation model is founded. In the model that water turbulence weakly satisfies a Laplacian distribution, it is demonstrated in the paper that the geometric distortion can be removed and a corrected image can be recovered. Then the image is partitioned into small patches which have partly overlapping between adjacent areas. Image quality assessment is used to make phases of image patches homomorphism. Image quality index method is used to image quality measurement in practice. Moreover, the phase average patches combine into a new image. At last the wiener filter is used to estimate the image which would have been observed without turbulence. The experimental result shows that the method can well realize restoration of images affected by turbulence and obtain a satisfactory effect, which can help the operator to carry out the visual inspection which underwater camera is used to achieve more accurate operation information of the fuel reloading.

A turbulence image restoration approach for visual inspection of nuclear power plants

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A turbulence image restoration approach for visual inspection of nuclear power plants