Refractive laser triangulation and photometric stereo in underwater environment

Abstract

Laser triangulation and photometric stereo are popular optical 3D reconstruction methods but bear limitations in underwater environment because of the refraction phenomenon. Refraction bends the usually straight rays of light to another directions in the interface of a flat underwater housing. It causes the camera to capture the virtual object points instead of the real ones, so that the commonly used pinhole camera model is invalid. Therefore, in this paper, we introduce a flat refractive model for describing the geometric relation accurately between the virtual object points and the real ones, which can correct the distortions in underwater 3D reconstruction methods. The parameters of model can be estimated in a calibration step with a standard chessboard. Then the proposed geometric relation is used for rebuilding underwater three-dimensional relationship in laser triangulation and photometric stereo. The experimental results indicate the effectiveness of our methods in underwater 3D reconstruction.Index Terms-refractive model, laser triangulation, photometric stereo.

State‐of‐the‐art in Multi‐Light Image Collections for Surface Visualization and Analysis

“…Another issue in underwater MLIC processing is related to light refraction effects. Fan et al [FQJ∗17] propose a flat refractive model to cope with this phenomenon by computing the mapping of virtual and real points; they are capable of removing distortions in underwater acquisitions both for 3D reconstruction and MLIC visualization.…”

Three-Dimensional Reconstruction with a Laser Line Based on Image In-Painting and Multi-Spectral Photometric Stereo

“…For the second issue, we could use a multi-spectral photometric stereo algorithm [ 8 , 9 , 10 ], which only needs a single-color image [ 11 , 12 , 13 , 14 ]. Finally, for the third issue, we could add a laser line on the RGB image, and correct the result of the multi-spectral photometric stereo algorithm through the height information of the pixels on the laser line [ 15 , 16 ].…”

“…Through the improvement of the network proposed by Isola [ 17 ], we proposed a network which can separate the multi-spectral image with a laser line into a clean laser image and an uncorrupted multi-spectral image without the laser line. And based on the proposed network and Fan’s [ 16 ] algorithm, we achieved accurate 3D reconstruction using a multispectral image with a laser line.…”

“…The main contributions of this article are summarized as follows: Through the improvement of the network proposed by Isola [ 17 ], we propose a Generative Adversarial Network based on image in-painting to realize the effective estimation of the pixel values at the locations covered by the laser line in the multi-spectral image; The proposed network can effectively extract the laser line in the multi-spectral image; Through adding certain U-Net-like structures to the generator of GAN, the proposed network can produce stable results; Based on the proposed network and Fan’s [ 16 ] algorithm, we achieve accurate 3D reconstruction using a multispectral image with a laser line. …”

“…Based on the proposed network and Fan’s [ 16 ] algorithm, we achieve accurate 3D reconstruction using a multispectral image with a laser line.…”