PROJECT TITLE :

Depth Map Reconstruction for Underwater Kinect Camera Using Inpainting and Local Image Mode Filtering - 2017

ABSTRACT:

Underwater optical cameras are widely used for security monitoring in ocean, like earthquake prediction and tsunami alarming. Optical cameras acknowledge objects for autonomous underwater vehicles and provide security protection for sea-floor networks. But, there are many issues for underwater optical imaging, like forward and backward scattering, light absorption, and ocean snow. Several underwater image processing techniques are proposed to beat these issues. Among these techniques, the depth map offers vital information for several applications of the post-processing. In this paper, we tend to propose a Kinect-based underwater depth map estimation method that uses a captured coarse depth map by Kinect with the loss of depth information. To beat the drawbacks of low accuracy of coarse depth maps, we tend to propose a corresponding reconstruction design that uses the underwater twin channels previous dehazing model, weighted enhanced image mode filtering, and inpainting. Our proposed method considers the influence of mud sediments in water and performs better than the ancient methods. The experimental results demonstrated that, once inpainting, dehazing, and interpolation, our proposed technique will create high-accuracy depth maps.