Second algorithm is based on the paper "Navier-Stokes, Fluid Dynamics, and Image and Video Inpainting". This algorithm is enabled by using Method = 'Telea'. It just works like a manual heuristic operation. FMM ensures those pixels near the known pixels are inpainted first, so that To next nearest pixel using Fast Marching Method. The point, near to the normal of the boundary and those lying on the boundary contours. More weightage is given to those pixels lying near to Selection of the weights is an important matter. This pixel is replaced by normalized weighted sum of all the known pixels It takes a small neighbourhoodĪround the pixel on the neigbourhood to be inpainted. Of this region and goes inside the region gradually filling everything in the boundary first. Consider a region in the image to be inpainted. (Additional algorithms are implemented in cv.inpaint2, part of opencv_contrib).įirst algorithm is based on the paper "An Image Inpainting Technique Based on the Fast Marching Method". Both can be accessed by the same function,Ĭv.inpaint. Several algorithms were designed for this purpose and OpenCV provides two of them. Those bad marks with its neighbouring pixels so that it looks like the neigbourhood. In these cases, a technique called image inpainting is used. Of restoring it back? We can't simply erase them in a paint tool because it is will simply replace black structures with white Most of you will have some old degraded photos at your home with some black spots or some strokes on it.
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