A Novel Method for Digital Orthophoto Generation from Top View Constrained Dense Matching

Abstract

The digital orthophoto is an image with both map geometric accuracy and image characteristics, which is commonly used in geographic information systems (GIS) as a background image. Existing methods for digital orthophoto generation are generally based on a 3D reconstruction. However, the digital orthophoto is only the top view of the 3D reconstruction result with a certain spatial resolution. The computation about the surfaces vertical to the ground and details less than the spatial resolution is redundant for digital orthophoto generation. This study presents a novel method for digital orthophoto generation based on top view constrained dense matching (TDM). We first reconstruct some sparse points using the features in the image sequence based on the structure-from-motion (SfM) method. Second, we use a raster to locate the sparse 3D points. Each cell indicates a pixel of the output digital orthophoto. The size of the cell is related to the required spatial resolution. Only some cells with initial values from the sparse 3D points are considered seed cells. The values of other cells around the seed points are computed from a top-down propagation based on color constraints and occlusion detection from multiview-related images. The propagation process continued until the entire raster was occupied. Since the process of TDM is on a raster and only one point is saved in each cell, TDM effectively eliminate the redundant computation. We tested TDM on various scenes and compared it with some commercial software. The experiments showed that our method’s accuracy is the same as the result of commercial software, together with a time consumption decrease as the spatial resolution decreases.