In nuclear power plants, it is a common procedure to use video inspection when reloading fuel assemblies regularly. Because of the turbulence generated by residual heat of nuclear fuel assemblies, a video sequence suffers from severe geometric deformations and is hard to be used to position the location hole of fuel assemblies. The paper proposes a novel algorithm to recover a geometrically correct image of nuclear fuel assemblies or scene from a video sequence distorted by turbulence underwater and achieve the precise position of the location hole. At the first, an average image is utilized to compare with image sequences to estimate nonrigid registration based on B-splines. By the estimated nonrigid registration, new image sequences are obtained and are used to get a new average image. After multiple iterations, the better image sequence can be shown. Then the better image sequence are divided into image patches. The more blurry and severely distorted image patches are removed in image patch sequences. Finally, the selected image patches are synthesized together. Based on restored images, template matching is utilized to quickly find the initial position of the location hole. And then the sub-pixel centroid method is used to achieve the sub-pixel position in the image. The calibrated camera parameters are utilized to calculate the position of the location hole of the fuel assemblies. Experiments verify that the algorithm can online locate the center of location holes on recovered images underwater, and has high measurement precision.
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.