New Methodologies for True Orthophoto Generation

Abstract

Orthophoto production aims at the elimination of sensor tilt and terrain relief effects from captured perspective imagery. Uniform scale and the absence of relief displacement in orthophotos make them an important component of GIS databases, where the user can directly determine geographic locations, measure distances, compute areas, and derive other useful information about the area in question. Differential rectification has been traditionally used for orthophoto generation. For large scale imagery over urban areas, differential rectification produces serious artifacts in the form of double mapped areas at object space locations with sudden relief variations, e.g., in the vicinity of buildings. Such artifacts are removed through true orthophoto generation methodologies which are based on the identification of occluded portions of the object space in the involved imagery. Existing methodologies suffer from several problems such as their sensitivity to the sampling interval of the digital surface model (DSM) as it relates to the ground sampling distance (GSD) of the imaging sensor. Moreover, current methodologies rely on the availability of a digital building model (DBM), which requires an additional and expensive pre-processing. This paper presents new methodologies for true orthophoto generation while circumventing the problems associated with existing techniques. The feasibility and performance of the suggested techniques are verified through experimental results with simulated and real data.

True Ortho Generation of Urban Area Using High Resolution Aerial Photos

“…Metrics Z-buffer (Amhar et al, 1998) Well-defined, widely accepted sensitive to GSD, false visibility Modified z-buffer (Rau et al, 2000) Fix false visibility Sensitive to GSD Sorted height (Habib et al, 2006) Simplest, easy to implement, no vertical walls Sensitive to GSD, false visibility, sorting Angle (Bang et al, 2007;Habib et al, 2007) Resolution independent Analyse one profile per pixel Angle & Height (Bang et al, 2007;Antequera, 2008) …”

“…Among multiple object points along the same line of sight competing for a single image pixel, the point closest to the perspective centre has the minimum distance value and is judged to be visible, while the other further points are considered invisible. Some modified variants of z-buffer have been proposed to conquer its drawbacks or to extend to rectify images taken by pushbroom sensors (Amhar et al, 1998;Rau et al, 2000;Nielsen, 2004;Oda et al, 2004;Bang et al, 2007;Habib et al, 2007;Chen et al, 2007;Antequera et., 2008;Bang and Kim, 2010).…”

System Considerations and Challendes in 3d Mapping and Modeling Using Low-Cost Uav Systems

“…Accurate registration of imagery data and laser scanning data, which is implemented during the system calibration procedure, has a great impact on effective utilization of laser-based point cloud for the generation of image-based point cloud. In addition, the image and point cloud data can be used to derive an accurate true ortho-photo mosaic, which will be obtained by simply projecting the colored point cloud on a specified datum (Ahmar et al, 1998;Habib et al, 2007). Different from the traditional true ortho-photos, which are produced by projecting the image data onto a horizontal datum, novel techniques have been developed to generate true orthophotos relative to any datum that will be specified by the users (Lari and Habib, 2015).…”

Generating a High-Precision True Digital Orthophoto Map Based on UAV Images

“…Moreover, a conventional orthophoto uses a digital elevation model (DEM), whereas a true orthophoto uses a digital surface model (DSM). Thus, TDOMs are rich in color, and simplify the identification of textural patterns [7][8][9][10][11][12][13][14][15]. …”