Super-resolution technique for dense 3D reconstruction in fringe projection profilometry

Fringe projection profilometry (FPP) is one of the most widely used 3D reconstruction techniques. A higher-resolution fringe pattern produces a more detailed and accurate 3D point cloud, which is critical for 3D sensing. However, there is no effective way to achieve FPP super-resolution except by using greater hardware. Therefore, this Letter proposes a dual-dense block super-resolution network (DdBSRN) to extend the fringe resolution and reconstruct a high-definition 3D shape. Especially, a novel dual-dense block structure is designed and embedded into a multi-path structure to fully utilize the local layers and fuse multiple discrete sinusoidal signals. Furthermore, a fully functional DdBSRN can be obtained even when training with a smaller data sample. Experiments demonstrate that the proposed DdBSRN method is stable and robust, and that it outperforms standard interpolation methods in terms of accuracy and 3D details. (C) 2021 Optical Society of America

Automated summary

Fringe projection profilometry is widely used for 3D reconstruction, but achieving super-resolution remains a challenge. The proposed dual-dense block super-resolution network aims to enhance fringe resolution and reconstruct high-definition 3D shapes effectively. Experimental results show that this method is stable and outperforms standard interpolation methods.