Hi, I found very few examples for transform.PolynomialTransform on the internet so I hope someone in this group can help me understand what I am doing wrong. If it's not the right place to ask for help, please forgive me! Here is my problem. I have a greyscale image with some curved lines. I want to transform it so the lines become straight. <https://lh3.googleusercontent.com/-l7PV-L6ZCek/VGsf6aKWYpI/AAAAAAAABSk/Pae2VGzGThY/s1600/test2.png> So I measure the position of the lines at regular intervals (in the attached file source_test2.csv) And compute the desired positions after transformation (in the attached file destination_test2.csv) So i have a nice set of input points and their correspondences as in the figure below (red = input points, and blue = desired positions after transformation): <https://lh4.googleusercontent.com/-2SjXbAQwJHU/VGsi-bqv8OI/AAAAAAAABSw/JsniNBo-Sok/s1600/corresponance.png> Next I compute the transformation using skimage.transform.PolynomialTransform and a polynomial of order 2, and apply the transformation to get the warped image using skimage.transform.warp But the warped image is completely crazy! See below: <https://lh3.googleusercontent.com/-VZmvMqQjNTo/VGsjdSpuklI/AAAAAAAABS4/OsAHobcF8dE/s1600/Crazy_Warped.png> It seems the transformation found by PolynomialTransform is completely wrong... *Note that I managed to get a good transformation in some cases for sub-images (e.g using the first 400 columns only).* What am I doing wrong? Are PolynomialTransform too unstable? Do I need a regular grid? I attach the code I use (warp.py) Thanks for your help! Hervé