The Telea method is based on the Fast Marching Method in which the algorithm starts from the boundary of the region to be inpainted and goes inside the region gradually filling the boundary first. flags: Algorithm to be used - INPAINT_TELEA or INPAINT_NS inpaintRadius: Radius of a circular neighborhood of each point inpainted that is considered by the algorithm 5. src: Input 8-bit 1-channel or 3-channel image. Here, we will be using OpenCV, which is an open-source library for Computer Vision, to do the same.Ĭv2.inpaint(src, inpaintMask, dst, inpaintRadius, flags) 1. These approaches fail when the size of the missing part is large, hence the need for deep neural networks to add an additional component that provides plausible imagination. The Diffusion-based approach propagates local structures into unknown parts while the Exemplar-based approach constructs the missing pixels one at a time while maintaining the consistency with the neighborhood pixels. Traditionally there are two approaches for this: Diffusion-based and Exemplar-based approaches. There are many techniques to perform Image Inpainting. In addition, it’s also possible to remove unwanted objects using Image Inpainting. This process is typically done manually in museums by professional artists but with the advent of state-of-the-art Deep Learning techniques, it is quite possible to repair these photos using digitally. Image Inpainting is the process of conserving images and performing image restoration by reconstructing their deteriorated parts. Photo by Jade Stephens on Unsplash What is Image Inpainting?
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