09-08-2025, 08:09 PM
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Images are one thing and maps are another. A map of the surface of earth has a specific projection and unless you are using the very same projection for both maps (in the case of some projections such as Lambert, the latitude/longitude of the center is important) they won't overlap when scaled.
Another problem when using random images is that the capture process may introduce distortion. Camera lenses have distortion (but these are well known and easy to fix, at least for "prime" lenses), while household/business scanners often have even more distortion, that is rarely mentioned and is complicated to fix.
So, your chance of having two maps of different origins differing only by a scale factor are abysmally small.
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Assuming you are talking about plain images (or identical map projections), when you use the Unified Transform tool you get the values of the transform matrix(*). Applying this matrix to the X,Y source coordinates will give you the X,Y coordinates of the target and vice-versa. You could have to invert the matrix.
Interpolation method is irrelevant. What it does is that when Gimp want to compute the value of a pixel at X,Y in the target, it uses the matrix to compute the X,Y value in the source. These are rarely integers, and the role of the interpolation method is, given an X,Y in the source, to compute the best possible value to apply to the target. Just rounding off is the "Nearest neighbor" or "None" algorithm, using a linear interpolation (5.33 would be two thirds of the pixel at 5 and one third of the pixel at 6) is the "Linear" one as you guess.
(*) Technically this matrix is used under the hood in all transform tools. But in simple tools it is best replaced by a simple concept, such as the scale factor or the rotation angle, so you have to use the UT to confront the matrix, which is the only thing of value to display. Using the UT could also allow you to fix and take in account small rotations/perspective (as far as they are introduced by the map reproduction/scan, not by the map projection itself).
Images are one thing and maps are another. A map of the surface of earth has a specific projection and unless you are using the very same projection for both maps (in the case of some projections such as Lambert, the latitude/longitude of the center is important) they won't overlap when scaled.
Another problem when using random images is that the capture process may introduce distortion. Camera lenses have distortion (but these are well known and easy to fix, at least for "prime" lenses), while household/business scanners often have even more distortion, that is rarely mentioned and is complicated to fix.
So, your chance of having two maps of different origins differing only by a scale factor are abysmally small.
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Assuming you are talking about plain images (or identical map projections), when you use the Unified Transform tool you get the values of the transform matrix(*). Applying this matrix to the X,Y source coordinates will give you the X,Y coordinates of the target and vice-versa. You could have to invert the matrix.
Interpolation method is irrelevant. What it does is that when Gimp want to compute the value of a pixel at X,Y in the target, it uses the matrix to compute the X,Y value in the source. These are rarely integers, and the role of the interpolation method is, given an X,Y in the source, to compute the best possible value to apply to the target. Just rounding off is the "Nearest neighbor" or "None" algorithm, using a linear interpolation (5.33 would be two thirds of the pixel at 5 and one third of the pixel at 6) is the "Linear" one as you guess.
(*) Technically this matrix is used under the hood in all transform tools. But in simple tools it is best replaced by a simple concept, such as the scale factor or the rotation angle, so you have to use the UT to confront the matrix, which is the only thing of value to display. Using the UT could also allow you to fix and take in account small rotations/perspective (as far as they are introduced by the map reproduction/scan, not by the map projection itself).