Super Resolving of the Depth Map for 3D Reconstruction of Underwater Terrain Using Kinect

In recent years, sonar has been widely used for restoring the underwater terrain. Sonar imaging has the benefits such as long-range photographing, robust for turbidity water. However, it is not suitable for short-range imaging. Meanwhile, it also cannot meet the need of mining machine. Therefore, it is important to develop a 3D reconstruction method for short-range imaging. In this paper, we propose a Kinect-based underwater 3D image reconstruction method. To overcome the drawbacks of low accuracy of depth maps, we propose a novel super-resolution (SR) method, which uses the underwater dark channel prior dehazing, weight guided image SR, and inpainting. The proposed method considered the influence of mud sediments in water, it performs better than the traditional methods. The experimental results demonstrated that, after inpainting, dehazing and the super-resolution, it can obtain high accuracy depth maps.

[1]  D. Lindsay,et al.  Management and use of multiple video formats and resolutions in ROVs , 2015 .

[2]  Huimin Lu,et al.  Underwater image dehazing using joint trilateral filter , 2014, Comput. Electr. Eng..

[3]  Huimin Lu,et al.  Contrast enhancement for images in turbid water. , 2015, Journal of the Optical Society of America. A, Optics, image science, and vision.

[4]  Jian-Ru Lin,et al.  3D underwater scene reconstruction through descattering and colour correction , 2016, Int. J. Comput. Sci. Eng..

[5]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[6]  Minh N. Do,et al.  Depth Video Enhancement Based on Weighted Mode Filtering , 2012, IEEE Transactions on Image Processing.

[7]  Alexandru Telea,et al.  An Image Inpainting Technique Based on the Fast Marching Method , 2004, J. Graphics, GPU, & Game Tools.