Image inpainting is the process of filling in missing regions in an image in a plausible way. In this contribution, we propose and describe an implementation of a patch-based image inpainting algorithm. The method is actually a two-dimensional version of our video inpainting algorithm proposed in [16]. The algorithm attempts to minimise a highly non-convex functional, first introducted by Wexle...

This paper describes the development of emerging colour interpolation techniques as GIMP plug-ins: Colouring Greyscale Images and Image Inpainting. The plug-ins will offer new image manipulation functionality that will enhance the capability of GIMP Colouring Greyscale Images refers to the ability to change the ‘mood’, colour information, of a greyscale image. The colorizing of the greyscale im...

Reconstruction of missing parts or scratches of digital images is an important field used extensively in artwork restoration. This restoration can be done by using two approaches, image inpainting and texture synthesis. There are many techniques for the two pervious approaches that can carry out the process optimally and accurately. In this paper the advantages and disadvantages of most algorit...

Image inpainting has been widely used in practice to repair damaged/missing pixels of given images. Most of the existing inpainting techniques require knowing beforehand where those damaged pixels are, either given as a priori or detected by some pre-processing. However, in certain applications, such information neither is available nor can be reliably pre-detected, e.g. removing random-valued ...

The image inpainting is a well-known task of visual editing. However, the efficiency strongly depends on sizes and textural neighborhood of “missing” area. Various methods of image inpainting exist, among which the Kohonen Self-Organizing Map (SOM) network as a mean of unsupervised learning is widely used. The weaknesses of the Kohonen SOM network such as the necessity for tuning of algorithm p...

Different from an orthonormal basis, a tight frame is an overcomplete and energy-preserving system with flexibility and redundancy. Many image restoration methods employing tight frames have been developed and studied in the literature. Tight wavelet frames have been proven to be useful in many applications. In this paper we are particularly interested in the image inpainting problem using dire...

Inpainting is the process of filling the missing regions in an image. The main aim of this paper is to fill the missing areas using examplar based inpainting and to recover the missing areas and improve the quality of the image using super resolution algorithm. The performance of the algorithm is evaluated using PSNR, mean square error and Histogram error. The damaged image is first downsampled...

We propose a framework for temporally consistent video completion. To this end we generalize the exemplar-based inpainting method of Criminisi et al . [7] to video inpainting. Specifically we address two important issues: Firstly, we propose a color and optical flow inpainting to ensure temporal consistency of inpainting even for complex motion of foreground and background. Secondly, rather tha...

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...

In 2-D image compression, recent approaches based on image inpainting with edge-enhancing anisotropic diffusion (EED) rival the transform-based quasi-standards JPEG and JPEG 2000 and are even able to surpass it. In this paper, we extend successful concepts from these 2-D methods to the 3-D setting, thereby establishing the first PDE-based 3-D image compression algorithm. This codec uses a cuboi...