HR Image Registration

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Image registration has been performed using the open source tool-set QGIS with its add on Georeference GDAL. The process to obtain the final aligned images are as follows:

  1. In QGIS, obtain intersection of both HR images by using the Clipper tool found under Raster → Extraction on the top toolbar. This here allows for a bounding box to be selected of the desired area.
  2. Using the Clipper tool again, divide the images up into 4 tiles. These tiles will be used with the Georeferencer tool. The need for dividing into sub-images is due to the Ground Control Points (GCP) needing to be plentiful in each georeferenced area. The alignment works by aligning these points of the moving and reference image and performing a transformation on the final image hence a smaller image results in more possible GCP's.
  3. Open Georeferencer tool under Raster → Georeferencer in the top toolbar. For each of the 4 sub-images of the aligning HR image, perform the following tasks:
    1. Load in one of the 4 aligning sub-image.
    2. With add point selected, select a point (usually of a structure) which can be used as a GCP. After choosing a point, select in the appearing window From map canvas. From here, select with the best approximation possible the same point on the reference image. Then, click okay and confirm this selection.
    3. Repeat step b. ~10 times for approximately evenly spaced points on the image.
    4. Now, select Settings → Transformation settings. Here, select Helmert transformation, Cubic resampling method and choose output raster directory. This will save the transformed aligned raster.
      *Note: Other transformations available including Poly, Projective etc. were all attempted. Helmert provided best result.
  4. Repeat step 3 4 times for the 4 tiles. After this is completed, go to Raster → Miscellaneous → Merge and merge these sub-images into 1 full image to obtain the final, aligned HR image.

The used GCP point data that can be loaded into the Georeferencer are found here: <a href="/confluence/download/attachments/75139161/top_1.tiff.points?version=1&modificationDate=1529755767976&api=v2" data-linked-resource-id="78711113" data-linked-resource-version="1" data-linked-resource-type="attachment" data-linked-resource-default-alias="top_1.tiff.points" data-linked-resource-content-type="application/octet-stream" data-linked-resource-container-id="75139161" data-linked-resource-container-version="5">top-subimage-1.points, </a><a href="/confluence/download/attachments/75139161/top_2.tiff.points?version=1&modificationDate=1529755768095&api=v2" data-linked-resource-id="78711114" data-linked-resource-version="1" data-linked-resource-type="attachment" data-linked-resource-default-alias="top_2.tiff.points" data-linked-resource-content-type="application/octet-stream" data-linked-resource-container-id="75139161" data-linked-resource-container-version="5">top-subimage-2.points</a>, <a href="/confluence/download/attachments/75139161/bottom_3.tiff.points?version=1&modificationDate=1529755767752&api=v2" data-linked-resource-id="78711111" data-linked-resource-version="1" data-linked-resource-type="attachment" data-linked-resource-default-alias="bottom_3.tiff.points" data-linked-resource-content-type="application/octet-stream" data-linked-resource-container-id="75139161" data-linked-resource-container-version="5">bottom-subimage.points</a>, <a href="/confluence/download/attachments/75139161/bottom_4.tiff.points?version=1&modificationDate=1529755767869&api=v2" data-linked-resource-id="78711112" data-linked-resource-version="1" data-linked-resource-type="attachment" data-linked-resource-default-alias="bottom_4.tiff.points" data-linked-resource-content-type="application/octet-stream" data-linked-resource-container-id="75139161" data-linked-resource-container-version="5">bottom-subimage-3.points</a>

Experimentation with results:

In pursuit of more consistent alignment of structures within collected image data, experimentation of using 10 more GCP points per sub-image was conducted (20 GCP total points/sub-image). This resulted in the following interesting observations:

  • Some areas containing structures suffered a worsened registration compared to the previous 10 GCP point alignment. Although, improvement is seen in the majority of the image.
  • Areas containing vineyards and other structures with simple, consistent geometric structures showed to contain almost No error after alignment. This was not an observed detail previously noted. When zooming in and performing visual inspection of vineyards across the ROI, they contain no unwanted translation from visual inspection. This is a very good result.