The invention relates to a true
orthophoto generation method based on a three-dimensional
Gaussian model, a storage medium and equipment, and aims to solve the problems of low
image quality, low generation speed, detail loss and the like in the prior art. The method comprises the following steps: firstly, acquiring image data through an unmanned aerial vehicle or
aerial photography, and extracting a camera attitude and sparse
point cloud by using a
motion recovery structure (SfM) technology; secondly, constructing a three-dimensional
Gaussian model based on the sparse
point cloud, and performing iterative training through top view
orthographic projection in combination with a
gradient descent algorithm; in the training process, a densification strategy, a point deleting strategy, a blocking strategy and an image
pyramid strategy are innovatively introduced, so that the detail expressive force and the overall quality of the image are remarkably improved. Specifically, according to the densification strategy, fine detail reconstruction is achieved by dynamically increasing
Gaussian ball density, and according to the point deletion strategy, rendering efficiency is improved and computing
resource allocation is optimized by eliminating redundant Gaussian balls. The image
pyramid strategy generates a multi-level visual effect through multi-scale training, and the blocking strategy improves the reconstruction precision through local optimization. Finally, on the basis of the trained three-dimensional Gaussian model, real-time generation of a high-quality true
orthophoto in a large-scale scene can be realized. The method has remarkable advantages in the aspects of efficiency, precision and practicability, provides important
technical support for the fields of geographic information systems,
urban planning,
disaster monitoring and the like, and has wide application prospects.