Image inpainting is a technique of filling unknown image region with known information from the surrounding of the unknown region in such a way that the result is logically accepted. Texture and structure completion in inpainting method is the main challenge in image inpainting and it is still an open problem to be tackled in the near future. In this paper, we propose a new inpainting algorithm...

In this paper, we propose a method for image compression in which currently developed vision technologies are incorporated with traditional transform-based coding methods. Based on newly developed vision technologies, we present two coding-oriented inpainting methods: structure-aware inpainting and object-based inpainting. Examples show the effectiveness of these inpainting methods on informati...

In applications like creating immersive walkthrough systems or digital reconstruction of invaluable artwork, both inpainting and super-resolution of the given images are the preliminary steps in order to provide better visual experience. The usual practice is to solve these problems independently in a pipelined manner. In this paper we propose a unified framework to perform simultaneous inpaint...

Digital image inpainting pertains to the reconstruction of missing or damaged portions of images in a manner that is not detectable to the observer. This study evaluates the Criminisi algorithm for digital image inpainting and proposes four improvements. First, a new priority function was introduced using piecewise function to adjust the sequence of inpainting process and change the operation u...

A Wiener-based inpainting quality prediction method is presented in this paper. The proposed method is the first method that can predict inpainting quality both before and after the intensities have become missing even if their inpainting methods are unknown. Thus, when the target image does not include any missing areas, the proposed method estimates the importance of intensities for all pixel...

Image inpainting is the process of filling in missing parts of damaged images based on information gleaned from surrounding areas. We consider a model for inpainting binary images using a modified Cahn–Hilliard equation. We prove for the steady state problem that the isophote directions are matched at the boundary of inpainting regions. Our model has two scales, the diffuse interface scale, ε, ...

In this paper we propose to use inpainting to estimate the severity of atherosclerotic plaques from X-ray projections. Inpainting allows to "remove" the plaque and estimate what the background image for an uncalcified aorta would have looked like. A measure of plaque severity can then be derived by subtracting the inpainting from the original image. In contrast to the current standard of catego...

We are often required to retouch images in order to improve their visual appearance, by removing the visual discontinuities like breaks and damaged regions. Such retouching of images may be achieved by inpainting. Current techniques for image inpainting require the user to manually select the target regions to be inpainted. Very few techniques for automatically detecting the target regions for ...

The filling in of missing region in an image is known as image inpainting. Image inpainting or completion is a technique to restore a damaged image. Now a days various techniques have been proposed. Wavelet transform is used for various image analysis problems due to its nice multi-resolution properties and decoupling characteristics. This paper proposed to utilize the advantages of wavelet tra...

Image inpainting is the art of predicting damaged regions of an image. The manual way of image inpainting is a time consuming. Therefore, there must be an automatic digital method for image inpainting that recovers the image from the damaged regions. In this paper, a novel statistical image inpainting algorithm based on Kriging interpolation technique was proposed. Kriging technique automatical...