Recovering lost part of an image plays a great role in image processing. Inpainting is a technique that helps in recovering lost pixels from an image. From the existing techniques of Inpainting, Exemplar Inpainting is one of the fast and better techniques that help in restoring the lost part of an image. Exemplar based method chooses a patch similar to the lost patch from the known area to fill...

In this paper, we propose a method to restore a single image affected by space-varying blur. The main novelty of our method is the use of recurring patterns as regularization during the restoration process. We postulate that restored patterns in the deblurred image should resemble other sharp details in the input image. To this purpose, we establish the correspondence of regions that are simila...

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...

We study the related problems of denoising images corrupted by impulsive noise and blind inpainting (i.e., inpainting when the deteriorated region is unknown). Our basic approach is to model the set of patches of pixels in an image as a union of low dimensional subspaces, corrupted by sparse but perhaps large magnitude noise. For this purpose, we develop a robust and iterative method for single...

AbstractImage inpainting or image retouching is the method of filling in or repairing the missing area of an image from the nearby pixels information by some algorithm. Its goal is to recover images with limited data loss and tries to obtain outputs of damaged area of an image in such a way that the recovered images look identical to original image. In our proposed method we will divide the dam...

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...

In this paper, a hybrid method for occlusion removal using Finite element based Bi-dimensional Empirical Mode Decomposition (FE-BEMD) and Exemplar based image inpainting is discussed. Initially, the image is decomposed into Intrinsic Mode Functions (IMFs) and a Residue using FEBEMD. Then the Exemplar based image inpainting algorithm is applied to each of the IMFs and residue and the results are...

The collection of electron energy loss spectra (EELS) via scanning transmission electron microscopy (STEM) generally requires a specimen to withstand a large radiation dose. Moreover, significant drift can occur while the spectra are collected. Recent advances in electron microscopy have shown that a data reduction of up to 90% is possible for HAADF/ABF imaging and TEM video [1, 2, 3]. These ad...