p-Laplace Variational Image Inpainting Model Using Riesz Fractional Differential Filter

In this paper, p-Laplace variational image inpainting model with symmetric Riesz fractional differential filter is proposed. Variational inpainting models are very useful to restore many smaller damaged regions of an image. Integer order variational image inpainting models (especially second and fourth order) work well to complete the unknown regions. However, in the process of inpainting with these models, any of the unindented visual effects such as staircasing, speckle noise, edge blurring, or loss in contrast are introduced. Recently, fractional derivative operators were applied by researchers to restore the damaged regions of the image. Experimentation with these operators for variational image inpainting led to the conclusion that second order symmetric Riesz fractional differential operator not only completes the damaged regions effectively, but also reducing unintended effects. In this article, The filling process of damaged regions is based on the fractional central curvature term. The proposed model is compared with integer order variational models and also GrunwaldLetnikov fractional derivative based variational inpainting in terms of peak signal to noise ratio, structural similarity and mutual information

Image Inpainting by Hyperbolic Selection of Pixels for Two Dimensional Bicubic Interpolations

Image inpainting is a restoration process which has numerous applications. Restoring of scanned old images with scratches, or removing objects in images are some of inpainting applications. Different approaches have been used for implementation of inpainting algorithms. Interpolation approaches only consider one direction for this purpose. In this paper we present a new perspective to image inpainting. We consider multiple directions and apply both one-dimensional and two-dimensional bicubic interpolations. Neighboring pixels are selected in a hyperbolic formation to better preserve corner pixels. We compare our work with recent inpainting approaches to show our superior results

Image Inpainting Algorithm for Region Filling Application

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Large block inpainting by color continuation analysis

[[abstract]]Automatic inpainting is a mechanism which repairs damaged pictures using an approximation mechanism. The most difficult problem is to inpaint a large damaged area, without knowing its content. One possible solution is to use color interpolation or extrapolation on surrounding pixels. However, spatial characteristics such as edges and pixel continuations are hard to be restored. In this research, we propose a series of automatic algorithms, which is based on an analysis of color continuations. Large damaged blocks are repaired, before the rest smaller potions are repaired by a multiresolution inpainting algorithm. The mechanism is tested on more than 2000 images, including cartoon drawing, photos, Chinese painting, and western painting. Our results prove that, the proposed automatic mechanism fixes damaged image up to a certain degree of satisfaction from the users. The demonstration of our work is available at: http://www.mine.tku.edu.tw/demos/inpaint.[[notice]]補正完畢[[conferencetype]]國際[[conferencedate]]20040105~20040107[[iscallforpapers]]Y[[conferencelocation]]Brisban, Australi

Comparative Analysis and Evaluation of Image inpainting Algorithms

Image inpainting refers to the task of filling in the missing or damaged regions of an image in an undetectable manner. There are a large variety of image inpainting algorithms existing in the literature. They can broadly be grouped into two categories such as Partial Differential Equation (PDE) based algorithms and Exemplar based Texture synthesis algorithms. However no recent study has been undertaken for a comparative evaluation of these algorithms. In this paper, we are comparing two different types of image inpainting algorithms. The algorithms analyzed are Marcelo Bertalmio’s PDE based inpainting algorithm and Zhaolin Lu et al’s exemplar based Image inpainting algorithm.Both theoretical analysis and experiments have made to analyze the results of these image inpainting algorithms on the basis of both qualitative and quantitative way. Keywords:Image inpainting, Exemplar based, Texture synthesis, Partial Differential Equation (PDE)

Investigation of Optimal Image Inpainting Techniques for Image Reconstruction and Image Restoration Applications

People in today's society take a lot of pictures with their smartphones and also make an effort to keep their old photographs safe, but with time, those photographs deteriorate. Image inpainting is the art of reconstructing damaged or missing parts of an image. Repairing scratches in photographs or film negatives, or adding or removing elements like stamped dates or "red-eye," are all possible through inpainting. In order to restore the image many techniques have been developed, significant techniques include exemplar based inpainting, coherent based inpainting and method for correction of non-uniform illumination. The four main applications of these image inpainting techniques are scratch removal, text removal, object removal and image restoration. However, all the four image inpainting applications cannot be implemented using a single technique. According to the literature, there has been relatively less work done in the field of image inpainting applications. Investigation has been carried out to find the suitability of these three techniques for the four above mentioned image inpainting applications based on two performance metrics