inpainting

Autoencoder-learned local image descriptor for image inpainting

In this paper, we propose an efficient method for learning local image descriptors suitable for the use in image inpainting algorithms. We learn the descriptors using a convolutional autoencoder network that we design such that the network produces a …

Image Inpainting and demosaicing via total variation and Markov random field-based modeling

The problem of image reconstruction from incomplete data can be formulated as a linear inverse problem and is usually approached using optimization theory tools. Total variation (TV) regularization has been widely applied in this framework, due to …

Big Data Processing in Artwork Analysis

Context-aware patch-based image inpainting using Markov random field modeling

In this paper, we first introduce a general approach for context-aware patch-based image inpainting, where textural descriptors are used to guide and accelerate the search for well-matching (candidate) patches. A novel top-down splitting procedure …

Digital image processing of the Ghent altarpiece: supporting the painting's study and conservation treatment

In this article, we show progress in certain image processing techniques that can support the physical restoration of the painting, its art-historical analysis, or both. We show how analysis of the crack patterns could indicate possible areas of …

Depth-guided patch-based disocclusion filling for view synthesis via Markov random field modelling

In this paper, we propose a novel patch-based disocclusion filling method for view synthesis from video-plus-depth data. The proposed method treats disocclusion filling as a global optimization problem, where global (spatial) consistency among the …

Markov random field based image inpainting with context-aware label selection

In this paper, we propose a novel global Markov Random Field based image inpainting method with context-aware label selection. Context is determined based on the texture and color features in fixed image regions and is used to distinguish areas of …

Texture and color descriptors as a tool for context-aware patch-based image inpainting

State-of-the-art results in image inpainting are obtained with patch-based methods that fill in the missing region patch-by-patch by searching for similar patches in the known region and placing them at corresponding locations. In this paper, we …