Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Fast Digital Orthophoto Generation: A Comparative Study of Explicit and Implicit Methods

Version 1 : Received: 18 December 2023 / Approved: 19 December 2023 / Online: 19 December 2023 (05:53:27 CET)

A peer-reviewed article of this Preprint also exists.

Lv, J.; Jiang, G.; Ding, W.; Zhao, Z. Fast Digital Orthophoto Generation: A Comparative Study of Explicit and Implicit Methods. Remote Sens. 2024, 16, 786. Lv, J.; Jiang, G.; Ding, W.; Zhao, Z. Fast Digital Orthophoto Generation: A Comparative Study of Explicit and Implicit Methods. Remote Sens. 2024, 16, 786.

Abstract

The digital orthophoto is an image with geometric accuracy and no distortion. It is acquired through a top view of the scene and finds widespread applications in map creation, planning, and related fields.This paper classifies the algorithms for digital orthophoto generation into two groups: explicit methods and implicit methods. Explicit methods rely on traditional geometric methods, obtaining geometric structure presented by explicit parameters with Multi-View Stereo (MVS) theories, as seen in our proposed Top view constrained Dense Matching (TDM). Implicit methods rely on neural rendering, obtaining implicit neural representation of scenes through the training of neural networks, as exemplified by Neural Radiance Fields (NeRF). Both of them obtain digital orthophoto by rendering from a top view perspective. In addition, this paper conducts an in-depth comparative study between explicit and implicit methods. The experiments demonstrate that both algorithms meet the measurement accuracy requirements and exhibit a similar level of quality in terms of generated results. Importantly, the explicit method shows a significant advantage in terms of efficiency, with a time consumption reduction of two orders of magnitude under our latest CUDA version TDM algorithm. Although explicit and implicit methods differ significantly in their representation forms, they share commonalities in the implementation across algorithmic stages. These findings highlight the potential advantages of explicit methods in orthophoto generation, while also providing beneficial references and practical guidance for the fast digital orthophoto generation using implicit methods.

Keywords

digital orthophoto; neural radiance fields; unmanned aerial vehicles

Subject

Computer Science and Mathematics, Computer Vision and Graphics

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