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 u...

Image inpainting technique uses textural or structural information to repair or fill damaged potions of a picture. When dealing with a small area missing textural image, not only should guarantee the effectiveness of the algorithm, but the processing speed also need to be taken into account. In this paper, we propose a simply and effective inpainting method which combining fast inpainting metho...

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...

Deep neural networks have been successfully applied to problems such as image segmentation, image super-resolution, coloration and image inpainting. In this work we propose the use of convolutional neural networks (CNN) for image inpainting of large regions in high-resolution textures. Due to limited computational resources processing high-resolution images with neural networks is still an open...

Recently, as 3D display devices become popular, automatic editing methods for stereoscopic image become important. In this paper, we propose an inpainting method for a stereoscopic image considering the texture similarity. By extending the conventional image inpainting method for an image considering the texture similarity to for a stereoscopic image by considering the consistency of two images...

Image inpainting is an important area in digital image processing, which has applications in problems like image restoration, scratch removal, or fluorescent microscopy. A lot of tools have been developed to tackle these problems. The total variation inpainting and the Euler’s elastica model are popular variational PDE methods in nontexture local image inpainting. The former is developed from t...

In spite of numerous works on inpainting, there has been little work addressing both image and structure inpainting. In this work, we propose a new method for inpainting both image and depth of a scene using multiple stereo images. The observations contain unwanted artifacts, which can be possibly caused due to sensor/lens damage or occluders. In such a case, all the observations contain missin...

Image inpainting is the technique of filling-in damaged regions by the surrounding information without affecting the contents and quality of the image i.e. restoration of an image using computers. Bertalmio proposed the first digital inpainting technique and coined the word ‘inpainting’ to the restoration work of digital images. Digital image inpainting is an interesting research topic and gath...

Image inpainting is a technique for restoring damaged old photographs and removing undesired objects from an image. The basic idea behind the technique is to automatically fill in lost or broken parts of an image using information from the surrounding area. The challenge of current inpainting algorithms is to restore both texture and structure characteristic information for large and thick dama...