Implementation of three algorithms of image deformation using moving least squares. http://dl.acm.org/citation.cfm?doid=1179352.1141920
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.
img_utils.py: Implementation of the algorithms
img_utils_demo.py: Demo program
read_tif.py: TIF file reader
tiff_deformation.py: Demo program
 Schaefer S, Mcphail T, Warren J. Image deformation using moving least squares[C]// ACM SIGGRAPH. ACM, 2006:533-540.