Sonar Image Generation from Underwater Optic Images utilizing Sensor Models and Depth Estimation with Neural Network
Minsung Sung, Son‐Cheol Yu · OCEANS 2021: San Diego – Porto · 2021
This paper proposes a method to generate a sonar image from an optical image, called optic-to-sonar which is one direction of opti-acoustic translation. To convert an optical image into a sonar image having a different geometry, the proposed method first reconstructs a three-dimensional point cloud by estimating the depth information using a neural network from given optical images. Then the sonar image is generated through the sonar projection model. We verified the proposed method through water tank experiments. The proposed method can generate a sonar image of the same viewpoint as a given optical image. So, it can be utilized as a dataset augmentation technique to further develop opti-acoustics in an underwater environment where data acquisition is challenging.