Image inpainting using multiresolution wavelet transform analysis

Digital image processing technique can be applied to virtual restoration of artistic paintings. This paper introduced a method for the restoration of digitized paintings which is based on wavelet transformation analysis. Initially the given image gets separated into two principal components which encompass image texture and image color, respectively. Then, using multiresolution characteristics of wavelet transform, from the lowest spatial-frequency layer to the higher one, the image is analyzed from global-area to local-area progressively. Then, variance of the energy of wavelet coefficients within each image block is used to decide the priority of inpainting blocks. Final step is to extract the multi-resolution features of each block. The correlation among horizontal, vertical and diagonal directions are considered, to determine the inpainting strategy for filling image pixels and approximate high-quality image inpainting to human vision. This method can be used for a variety of input images that exhibit different kinds of defects.