Abstract

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.

© 2021 Optical Society of America

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