Traditional Photogrammetric Workflow

Photogrammetric workflow commonly refers to the analog frame camera workflow. Analog frame cameras were prevalent prior to digital photography and remain a common source of imagery. Numerous software tools have been developed to guide users through the traditional analog frame workflow. The mainstream analog frame workflow is listed below:

Scanning:

Airborne camera film is scanned and converted into a digital file format using high precision photogrammetric scanning equipments.

Dodging:

The scanning process may introduce radiometric distortions such as hotspots and vignetting. These can be minimized by applying a dodging algorithm, generally calculates a set of input statistics describing the radiometry of a group of images and then, generates target output values for every input pixel and the pixels are then shifted based on the parameters and constraints given.

Project initiation:

The photogrammetric packages invariably have an initialization which defines the system with general information about the project. Ancillary information may include data such as flying height, sensor type, the rotation system, and photo direction

Camera Information:

The user needs to provide information about the camera used during the time of image acquisition. The information is stored in an external “camera file” and may be used further after it is defined initially. It contains information such as focal length, principal point offset, fiducial mark information, and radial lens distortion.

Interior Orientation (IO):

The interior orientation process relates film coordinates to the image coordinates.

Aerial Triangulation (AT):

This process orient images in the project to one another by solving the orientation parameters (X, Y, Z, omega, phi, kappa) for each image. True ground coordinates will also be established. The AT process is a time-consuming, critical component of the photogrammetry workflow. Sub-components of the AT process are:
- Measuring ground control points (typically surveyed points)
- Establishing an initial approximation of the orientation parameters (rough orientation)
- Measuring tie points (this is often an automatic procedure in digital photogrammetry systems)
- Performing the bundle adjustment
- Refining the solution: remove or re-calculate inaccurate points until the solution is within the tolerance limit.

Terrain Generation:

Accurate terrain models are absolutely necessary for generation of digital orthophotos. Terrain models can be in the form of Triangulated Irregular Network (TINs) or grids. After Aerial Triangulation, the terrain generation can typically be run as an automatic process in most photogrammetric packages. Manually extracted vector files, control points, or other data can also be input to guide the correlation process. Filtering can be used for the removal of surface features like buildings and trees. Terrain can also be acquired via manual compilation (in stereo), LIDAR, or publicly available datasets like SRTM.

Terrain Editing:

Digital Terrain Models (DTMs) generated by autocorrelation procedures require some editing to model the terrain. In the process it is important for the analyst to see the terrain in stereo so that they can determine if automatically generated terrain posts are on the surface the DTM is enough accurate representation of the terrain for the specific project. Terrain can usually be rendered using a mesh, contours, points, and breaklines. Terrain editing tools for TIN and grid terrain models include post editing, adjust Z for grid cells, area tools for smoothing, surface fitting operations, spike and well removal tools and geomorphic tools. After completing the editing process the user may have to convert it into a customer-specified output format (e.g. one TIN format to another, or TIN to grid).

Feature Extraction:

Feature extraction is an optional step in the workflow, depending on the specifications of the project. Manual stereo extraction is the common method used to collect, edit and attribute point, line, and polygonal features.

Orthophoto Generation:

There are many different specifications for Orthophotos, including accuracy, radiometric quality, GSD, tile definitions, projection, and file format. Generally, orthophoto production follows these steps: Input image selection and Terrain source selection followed by options like the image resampling method, projection, and output coordinates.

Ortho Mosaicking:

A mosaicking process is included in the ortho workflow to produce a smooth, seamless, and radiometrically acceptable product for the entire project area. Mosaicking may be performed as part of the orthophoto process directly (orthomosaicking) or performed as a postprocess later. The mosaicking process involves constant operator interaction. After images are chosen for the mosaic process, define seams by polygons or lines to determine which areas of the input images will be used in the output mosaic. Operators will typically edit the seams so that they do not cut through well-defined features such as buildings. The ultimate goal of seam editing is to “hide” the seams so they are not visible in the output mosaic. Once seams are defined, they can usually have smoothing or feathering operations applied to them so that their appearance is minimized. Another important aspect is radiometric correction and the goal is to make radiometrically homogeneous output images.

Tiling:

A project area may be several hundred square kilometers in size, so a single output mosaic file is not usually possible to handle easily. End customers would prefer their digital orthomosaic in a series of tiles defined by their own specifications. Photogrammetric systems have methods for defining a tiling scheme to produce a seamless tiled output.