Object Removal | PatchMatch | ANN | NNF | python implementation
Removing an object (e.g., a bison, a cow, a street lamp, a bush or even a shadow, specified with a binary mask) from an image using PatchMatch algorithm - an implementation (of the unconstrained version) in python
The algorithm randomly initializes an ANNF (approximate nearest neighbor field)
The ANNF is improved with propagation (with spatial coherence assumption) and random search (by gradually reducing the search radius and randomly sampling pixels within the radius as matching candidate patches) steps iteratively
For object removal, the matching patches (with a given size) outside the mask votes for the missing region
An EM (expectation maximization) style algorithm is used to iteratively update the image and the mask (shrinking it), as well as improving the ANN field. As can be seen, the distances for the NNF gets updated over iterations
#python #imageprocessing #imageprocessingpython #computervision #algorithm
Ref: https://gfx.cs.princeton.edu/pubs/Bar...
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