Image In-painting by Band Matching, Seamless Cloning and Area Sub-division

We propose a novel image in-painting method composed of two parts: band matching and seamless cloning. In band matching, a band enclosing the boundary of a missing region is compared to those from the other parts of the image. The inner area of the minimum difference band is then copied to the missing region. Even though this band matching results in successful inpainting in many practical applications, brightness discontinuity (a seam) may appear between the filled missing region and its neighborhood. We apply seamless-cloning to remove such discontinuity between the two regions. Examples show that this two step approach can provide a very fast and effective image in-painting. However, since this basic method using one patch may not deal with cases where there are abrupt changes of color or brightness along the boundary, we furthermore devise one more step: target sub-division. The target area is subdivided into small sub-areas, and the band matching and seamless cloning is applied to each of them. This sub-division is done also when the missing region is too large or the user wants to see more candidates to choose a better one. The multiple results from the sub-division are then ordered according to in-painting quality, which is measured based the edge map or discontinuity map along the boundary band. Our algorithm is demonstrated with various experiments using real images.