Exemplar-based image inpainting using ISEF for priority computation

Inpainting is an art of restoring damages or removal and filling in removed region. Exemplar-based techniques simply fill target region iteratively using best matching patch from rest of the image. An important part of this model is data term which decides order of filling procedure. In most of the methods, data term depends on strength of an isophote which is found from gradient operator. Gradient operator is a poor numerical differentiation based approximation of edges. In this paper, a new data term is proposed which is based on gradient obtained by application of Infinite size Symmetric Exponential Filter (ISEF). ISEF is a one-step based multi-edge model which detects edges by differentiation of optimal exponential and obtained edges help to preserve structure information. New ISEF based data term improves ordering of patches and helps preventing linear and curved structures. Proposed method has been applied to various images containing structure and composite structure. It can be seen that proposed method produces comparable results. Experimental results show that proposed method not only improves visual quality but also improves Peak Signal-to-Noise Ratio (PSNR) which is considered as a quantitative measure.