An Image Inpainting Algorithm Using Higher Order Singular Value Decomposition

In this paper, we present an exemplar-based image in painting technique using the higher order singular value decomposition (HOSVD). The two main steps of the proposed method are determination of patch priority and patch completion. Here we adopt gradient-based priority term. For patch completion, we build a stack of the candidate patches corresponding to the target patch. Then we find the coefficients matrix of singular values using HOSVD transformation from the stack and nullify some singular values which corresponds to some artifacts. Next, we invert the HOSVD transform and synthesize the target patch by taking weighted average of filtered candidate patches. We also incorporate local patch consistency in the proposed model. Experimental results show the superiority of the proposed method compared to the competitive methods. The proposed method may be used for restoration of digital images of defective or damaged artifacts.