HomologousPointsExtraction - Homologous Points Extraction¶
Compute homologous points between images using keypoints
This application allows computing homologous points between images using keypoints. SIFT or SURF keypoints can be used and the band on which keypoints are computed can be set independently for both images. The application offers two modes : the first is the full mode where keypoints are extracted from the full extent of both images (please note that in this mode large image file are not supported). The second mode, called geobins, allows one to set-up spatial binning to get fewer points spread across the entire image. In this mode, the corresponding spatial bin in the second image is estimated using geographical transform or sensor modelling, and is padded according to the user defined precision. Last, in both modes the application can filter matches whose colocalisation in first image exceed this precision. The elevation parameters are to deal more precisely with sensor modelling in case of sensor geometry data. The outvector option allows creating a vector file with segments corresponding to the localisation error between the matches. It can be useful to assess the precision of a registration for instance. The vector file is always reprojected to EPSG:4326 to allow display in a GIS. This is done via reprojection or by applying the image sensor models.
This section describes in details the parameters available for this application. Table  presents a summary of these parameters and the parameters keys to be used in command-line and programming languages. Application key is HomologousPointsExtraction .
|||Table: Parameters table for Homologous Points Extraction.|
|Parameter Key||Parameter Name||Parameter Type|
|in1||Input Image 1||Input image|
|band1||Input band 1||Int|
|in2||Input Image 2||Input image|
|band2||Input band 2||Int|
|algorithm||Keypoints detection algorithm||Choices|
|algorithm surf||SURF algorithm||Choice|
|algorithm sift||SIFT algorithm||Choice|
|threshold||Distance threshold for matching||Float|
|backmatching||Use back-matching to filter matches.||Boolean|
|mode||Keypoints search mode||Choices|
|mode full||Extract and match all keypoints (no streaming)||Choice|
|mode geobins||Search keypoints in small spatial bins regularly spread across first image||Choice|
|mode.geobins.binsize||Size of bin||Int|
|mode.geobins.binsizey||Size of bin (y direction)||Int|
|mode.geobins.binstep||Steps between bins||Int|
|mode.geobins.binstepy||Steps between bins (y direction)||Int|
|mode.geobins.margin||Margin from image border to start/end bins (in pixels)||Int|
|precision||Estimated precision of the colocalisation function (in pixels).||Float|
|mfilter||Filter points according to geographical or sensor based colocalisation||Boolean|
|2wgs84||If enabled, points from second image will be exported in WGS84||Boolean|
|elev.geoid||Geoid File||Input File name|
|out||Output file with tie points||Output File name|
|outvector||Output vector file with tie points||Output File name|
|inxml||Load otb application from xml file||XML input parameters file|
|outxml||Save otb application to xml file||XML output parameters file|
Input Image 1: First input image.
Input band 1: Index of the band from input image 1 to use for keypoints extraction.
Input Image 2: Second input image.
Input band 2: Index of the band from input image 1 to use for keypoints extraction.
Keypoints detection algorithm: Choice of the detection algorithm to use. Available choices are:
- SURF algorithm
- SIFT algorithm
Distance threshold for matching: The distance threshold for matching.
Use back-matching to filter matches.: If set to true, matches should be consistent in both ways.
Keypoints search mode Available choices are:
- Extract and match all keypoints (no streaming): Extract and match all keypoints, loading both images entirely into memory.
- Search keypoints in small spatial bins regularly spread across first image: This method allows retrieving a set of tie points regulary spread across image 1. Corresponding bins in image 2 are retrieved using sensor and geographical information if available. The first bin position takes into account the margin parameter. Bins are cropped to the largest image region shrunk by the margin parameter for both in1 and in2 images.
- Size of bin: Radius of the spatial bin in pixels.
- Size of bin (y direction): Radius of the spatial bin in pixels (y direction). If not set, the mode.geobins.binsize value is used.
- Steps between bins: Steps between bins in pixels.
- Steps between bins (y direction): Steps between bins in pixels (y direction). If not set, the mode.geobins.binstep value is used.
- Margin from image border to start/end bins (in pixels): Margin from image border to start/end bins (in pixels).
Estimated precision of the colocalisation function (in pixels).: Estimated precision of the colocalisation function in pixels.
Filter points according to geographical or sensor based colocalisation: If enabled, this option allows one to filter matches according to colocalisation from sensor or geographical information, using the given tolerancy expressed in pixels.
If enabled, points from second image will be exported in WGS84
[Elevation management]: This group of parameters allows managing elevation values. Supported formats are SRTM, DTED or any geotiff. DownloadSRTMTiles application could be a useful tool to list/download tiles related to a product.
- DEM directory: This parameter allows selecting a directory containing Digital Elevation Model files. Note that this directory should contain only DEM files. Unexpected behaviour might occurs if other images are found in this directory.
- Geoid File: Use a geoid grid to get the height above the ellipsoid in case there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles. A version of the geoid can be found on the OTB website (https://git.orfeo-toolbox.org/otb-data.git/blob/HEAD:/Input/DEM/egm96.grd).
- Default elevation: This parameter allows setting the default height above ellipsoid when there is no DEM available, no coverage for some points or pixels with no_data in the DEM tiles, and no geoid file has been set. This is also used by some application as an average elevation value.
Output file with tie points: File containing the list of tie points.
Output vector file with tie points: File containing segments representing matches .
Load otb application from xml file: Load otb application from xml file.
Save otb application to xml file: Save otb application to xml file.
To run this example in command-line, use the following:
otbcli_HomologousPointsExtraction -in1 sensor_stereo_left.tif -in2 sensor_stereo_right.tif -mode full -out homologous.txt
To run this example from Python, use the following code snippet:
#!/usr/bin/python # Import the otb applications package import otbApplication # The following line creates an instance of the HomologousPointsExtraction application HomologousPointsExtraction = otbApplication.Registry.CreateApplication("HomologousPointsExtraction") # The following lines set all the application parameters: HomologousPointsExtraction.SetParameterString("in1", "sensor_stereo_left.tif") HomologousPointsExtraction.SetParameterString("in2", "sensor_stereo_right.tif") HomologousPointsExtraction.SetParameterString("mode","full") HomologousPointsExtraction.SetParameterString("out", "homologous.txt") # The following line execute the application HomologousPointsExtraction.ExecuteAndWriteOutput()
Full mode does not handle large images.
- These additional resources can be useful for further information: