Natural image statistics exhibit hierarchical dependencies across multiple scales. Representing such prior knowledge in non-factorial latent tree models can boost performance of image denoising, inpainting, deconvolution or reconstruction substantially, beyond standard factorial “sparse” methodology. We derive a large scale approximate Bayesian inference algorithm for linear models with nonfact...

In this article we discuss the implementation of the combined first and second order total variation inpainting that was introduced in [19]. We describe the algorithm we use (split Bregman) in detail and we give some examples that indicate the difference between pure first and pure second order total variation inpainting. Finally we provide a source code for the algorithm written in C and an on...

Although tremendous advancement happen in image processing domain, still “filling the missing areas” is area of concern in it. Though lot of progress has been made in the past years, still lot of work should be done. A novel algorithm is presented for examplar-based inpainting. In the proposed algorithm initially inpainting is applied on the coarse version of the input image, latter hierarchica...

Reconstructing the missing parts of a curve has been the subject of much computational research, with applications in image inpainting, object synthesis, etc.. Different approaches for solving that problem are typically based on processes that seek visually pleasing or perceptually plausible completions. In this work we focus on reconstructing the underlying physically likely shape by utilizing...

This paper proposes a novel scheme for digital images inpainting based on discrete wavelet transform (DWT). Where the digital image is decomposed into four components and both structure and exemplar inpainting methods are individually applied on them to obtain the best arrangement with each component. Many cases if digital image have been used to verify the scheme. The aim of this research is t...

—In the digital world, inpainting is the algorithm used to replace or reconstruct lost, corrupted, or deteriorated parts of image data. Of the various proposed inpainting methods, convolutional methods are the simplest and most efficient. In this paper, an enhanced inpainting model based on convolution theorem is proposed for digital images that preserves the edge and effectively estimates the...