Image In-painting, the technique that aims to revert deterioration (scratches, artifacts in photographs and videos) in images in an undetectable form, is as ancient as artistic creation itself. Digital Image In painting, a relatively young research area is an art of filling in the missing or corrupted regions in an image using information from the neighbouring pixels in a visually plausible manner, while restoring its unity. In painting which is essentially an image interpolation problem has numerous applications. It is helpfully used for object removal in digital photographs, image reconstruction, text removal, video restoration, special effects in movies disocclusion and so on. Several approaches have been proposed by the researchers to correct the occlusion. This proposed work presents a comparative study to provide a comprehensive visualization of different image in painting techniques. In this paper different types of image in painting algorithms are placed in juxtaposition. The algorithms are analysed theoretically as well as experimentally, based on which a ranking of algorithms will be established over different kinds of applications in diverse areas .
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