Bayesian | α-matting | python implementation
Bayesian α-matting for images - an implementation with python
by solving linear system of equations for each of the unknown pixels in the input image, the ones marked in gray in the trimap image, to obtain F (foreground), B (background) and α (matte), by iteratively maximizing the posterior log-likelihood.
system of equation is obtained by computing the posterior with the data term representing fidelity to the matting equation I = αF + (1-α)B and the Gaussian priors on the Foreground and Background (with MLE parameter estimates).
ref: https://grail.cs.washington.edu/proje...
digital-matting/papers/cvpr2001.pdf) and youtube lecture video by Rich Radhke
#imageprocessing #imageprocessingpython #matting #bayesian
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