In many cases inpainting methods introduce a blur in sharp transitions in image and image contours in the recovery of large areas with missing pixels and often fail to recover curvy boundary edges. Quantitative metrics of inpainting results currently do not exist and researchers use human comparisons to evaluate their methodologies and techniques. Most objective quality assessment methods rely ...

The inpainting of damaged images has a wide range of applications and many different mathematical methods have been proposed to solve this problem. Inpainting with the help of Cahn-Hilliard models has been particularly successful, and it turns out that Cahn-Hilliard inpainting with the double obstacle potential can lead to better results compared to inpainting with a smooth double well potentia...

Kinect sensors or cameras be used here most recent automatic scheme used for selection of applications for instance gaming, facilitation of communication also health care on behalf of intensity amount of an environment under scanning at a higher frame rate. The kinect sensor generally make use of infrared light as a source of scanning the object, So the crisis in the system comes from the fact ...

In the context of video editing, enforcing spatio-temporal consistency is an important issue. With that purpose, the current variational models for gradient domain video editing include space and time regularization terms. The spatial terms are based on the usual space derivatives, the temporal ones are based on the convective derivative, and both are balanced by a parameter β. However, the usu...

Scene-agnostic visual inpainting remains very challenging despite progress in patch-based methods. Recently, Pathak et al. [25] have introduced convolutional “context encoders” (CEs) for unsupervised feature learning through image completion tasks. With the additional help of adversarial training, CEs turned out to be a promising tool to complete complex structures in real inpainting problems. ...

Recent research has shown that inpainting with the Laplace or biharmonic operator has a high potential for image compression, if the stored data is optimised and sufficiently sparse. The goal of our paper is to connect these linear inpainting methods to sparsity concepts. To understand these relations, we explore the theory of Green’s functions. In contrast to most work in the mathematical lite...

The problem of inpainting involves reconstructing the missing areas of an image. Inpainting has many applications, such as reconstructing old damaged photographs or removing obfuscations from images. In this paper we present the directional diffusion algorithm for inpainting. Typical diffusion algorithms are bad at propagating edges from the image into the unknown masked regions. The directiona...

The Cahn-Hilliard equation has its origin in material sciences and serves as a model for phase separation and phase coarsening in binary alloys. A new approach in the class of fourth order inpainting algorithms is inpainting of binary images using the Cahn-Hilliard equation. We will present a generalization of this fourth order approach for grayvalue images. This is realized by using subgradien...

The aim of this article is to propose a new method for the inpainting problem. Inpainting is the problem of filling-in holes in images. We consider in this article the crack localization problem, which can be solved using the Dirichlet to Neumann approach and the topological gradient. In a similar way, we can define a Dirichlet and a Neumann inpainting problem. We then define a cost function me...