Update: 2020-09-25 No need for so-called inverse transformation. Just transform target pixels to the corresponding source pixels.
Moving least squares is a method of reconstructing continuous functions from a set of unorganized point samples via the calculation of a weighted least squares measure biased towards the region around the point at which the reconstructed value is requested.
In computer graphics, the moving least squares method is useful for reconstructing a surface from a set of points. Often it is used to create a 3D surface from a point cloud through either downsampling or upsampling.
- Affine deformation
- Similarity deformation
- Rigid deformation
- Toy
- Monalisa
- Cells
img_utils.py
: Implementation of the algorithmsimg_utils_demo.py
: Demo programread_tif.py
: TIF file readertiff_deformation.py
: Demo program
[1] Schaefer S, Mcphail T, Warren J. Image deformation using moving least squares[C]// ACM SIGGRAPH. ACM, 2006:533-540.