Underwater imaging poses significant challenges due to random dynamic distortions caused by reflection and refraction of light through the water waves. Moving object detection in a turbulent medium further imposes complexity in the imaging. In this paper, a new approach is proposed for turbulence compensation of a distorted underwater video while keeping the real motions unharmed. First, a geometrically stable frame is created from the distorted video that contains no moving objects. Then, a robust non-rigid image registration technique is used to estimate the motion vector fields of the distorted frames against the stable frame. The difference images of the distorted frames with respect to the stable frame, and the estimated motion vector fields are used to detect the real motion regions and to generate a mask for each frame to extract those regions. This proposed method is compared with an earlier method through both qualitative and quantitative analysis. Simulation experiments show that the proposed method provides better corrections to the effects of underwater turbulence whilst accurately preserving the moving objects.
This paper presents an algorithm for recovering an image from a sequence of distorted versions of it, where the distortions are caused by a wavy water surface. A robust non-rigid image registration technique is employed to determine the pixel shift maps of all the frames in the sequence against a reference frame. An iterative image dewarping algorithm is applied to correct the geometric distortions of the sequence. A non-local means filter is used to mitigate noise and improve the signal-to-noise ratio (SNR). The performance of our proposed method is compared against the state-of-the-art method. Results show that our proposed method performs significantly better in removing geometric distortions of the underwater images.