Iterative Gradient-Driven Patch-Based Inpainting (original) (raw)

Quality Improvement for Exemplar-based Image Inpainting using a Modified Searching Mechanism

UHD Journal of Science and Technology

Digital image processing has a significant impact in different research areas including medical image processing, biometrics, image inpainting, object detection, information hiding, and image compression. Image inpainting is a science of reconstructing damaged parts of digital images and filling-in regions in which information are missing which has many potential applications such as repairing scratched images, removing unwanted objects, filling missing area, and repairing old images. In this paper, an image inpainting algorithm is developed based on exemplar, which is one of the most important and popular images inpainting technique, to fill-in missing area that caused either by removing unwanted objects, by image compression, by scratching image, or by image transformation through internet. In general, image inpainting consists of two main steps: The first one is the priority function. In this step, the algorithm decides to select which patch has the highest priority to be filled ...

Patch based Image Inpainting Technique Using Adaptive Patch Size and Sequencing of Priority Terms

International Journal of Image, Graphics and Signal Processing, 2019

Image Inpainting is a system used to fill lost information in an image in a visually believable manner so that it seems original to the human eye. Several algorithms are developed in the past which tend to blur the inpainted image. In this paper, we present an algorithm that improves the performance of patch based image inpainting by using adaptive patch size and sequencing of the priority terms. The patch width (wxw) is made adaptive (proportional) to the area of the damaged region and inversely proportional to standard deviation of the known values in the patch around point of highest priority. If the neighbourhood region is a smooth region then standard deviation is small therefore large patch size is used and if standard deviation is large patch size is small. The algorithm is tested for various input images and compared with some standard algorithm to evaluate its performance. Results show that the time required for inpainting is drastically reduced while the quality factor is maintained equivalent to the existing techniques.

Exemplar-Based Image Inpainting Technique using Image Partitioning (Search Region Prior) Method

Exemplar based image inpainting is a combine effect of texture and structure syntheses. This technique can be applicable by applying Basic traditional method (Criminisi algorithm) Patch shifting scheme, Search region prior method. Criminsi’algorithm is based upon isophote-driven image sampling process, gives better image quality but require more time to inpaint damage region. Sarawut’s patch shifting scheme, shift the target patch towards source region having more information related to missed region, PSNR improved but time requirement is more than criminsi’s method. After analyzing, both above given method, proposed method based on K-means clustering reduced time complexity and improve image quality also

Exemplar based Image Inpainting with Reduced Search Region

International Journal of Computer Applications, 2014

Image inpainting is a technique to recover lost data or manually remove data from an image. This process is carried out in such a way that it seems reasonable to human eyes. The lost part of the image is filled with the remaining available data of the image. Inpainting can be done using various techniques, mainly variation based, exemplar based and wavelet based. In this paper, exemplar based image inpainting techniques is used and an algorithm which improves and extends the previously proposed algorithm is presented. Instead of searching the entire image, the proposed approach has reduced the search region by searching the nearby pixels since most of the relevant information lies in neighbouring pixels which reduces time to complete inpainting. This technique is mainly used for removing objects and cracks from the image.

A Survey on Exemplar-Based Image Inpainting Techniques

Preceding paper include exemplar-based image inpainting technique give idea how to inpaint destroyed region such as Criminisi algorithm, patch shifting scheme, search region prior method. Criminsi’s and Sarawut’s patch shifting scheme needed more time to inpaint an damaged region but proposed method decrease time complexity by searching only in related region of missing portion of image.

A Comparative Analysis of Exemplar Based Image Inpainting Algorithms

European Journal of Scientific …, 2011

Image inpainting refers to the task of filling in the missing or damaged regions of an image in an undetectable manner. Many researchers have proposed a large variety of exemplar based image inpainting algorithms to restore the structure and texture of damaged images. However no recent study has been undertaken for a comparative evaluation of these algorithms. In this paper, we are comparing various exemplar based image inpainting algorithms which do not have diffusion related blur in the result image. The analyzed algorithms are Antonio Criminisi et al's Region filling algorithm, Jiying Wu et al's Hybrid algorithm and Zhaolin Lu et al's Image completion algorithm. Both theoretical analysis and experiments have made to analyze the results of these exemplar based image inpainting algorithms on the basis of Peak Signal to Noise Ratio (PSNR).

Novel Approach for Image Inpainting

IJSRD, 2014

This presents a novel and efficient examplarbased inpainting algorithm through investigating the sparsity of natural image patches. Two novel concepts of sparsity at the patch level are proposed for modeling the patch priority and patch representation, which are two crucial steps for patch propagation in the examplar-based inpainting approach. First, patch structure sparsity is designed to measure the confidence of a patch located at the image structure the sparseness of its nonzero similarities to the neighboring patches. The patch with larger structure sparsity will be assigned higher priority for further inpainting. Second, it is assumed that the patch to be filled can be represented by the sparse linear combination of candidate patches under the local patch consistency constraint in a framework of sparse representation. Compared with the traditional examplar-based inpainting approach, structure sparsity enables better discrimination of structure and texture, and the patch sparse representation forces the newly inpainted regions to be sharp and consistent with the surrounding textures.

Image Inpainting Based on Local Optimisation

In this paper, we tackle the problem of image inpainting which aims at removing objects from an image or repairing damaged pictures by replacing the missing regions using the information in the rest of the scene. The image inpainting method proposed here builds on an exemplar-based perspective so as to improve the local consistency of the inpainted region. This is done by selecting the optimal patch which maximises the local consistency with respect to abutting candidate patches. The similarity computation generates weights based upon an edge prior and the structural differences between inpainting exemplar candidates. This treatment permits the generation of an inpainting sequence based on a list of factors. The experiments show that the proposed method delivers a margin of improvement as compared to alternative methods.

Introducing a new fast exemplar-based inpainting algorithm

Inpainting is the process of reconstructing damaged parts of an image in a visually plausible way. Recently, digital image inpainting has been an active field of research in the area of image processing. Meanwhile, exemplar-based methods have had a major contribution in developing this field of research. The main idea in these methods is based on copy-and-paste texture synthesis. The time-complexity of these methods are rather high. So, many different approaches were introduced to tackle this problem. This paper presents a new algorithm for reconstructing missing parts of an image based on exemplar-matching techniques in which both performance and speed of the algorithm increases. Experimental results confirm the effectiveness of the proposed method.

The Proposal of a New Image Inpainting Algorithm

In the domain of image inpainting or retouching, many recent works focus on combining methods of different fields of research in order to obtain more accurate results, and more original images. In this paper we propose a new algorithm that combines three different methods, each one represent a separate field. The first one for the use of artificial intelligence, the second one for the use of the partial differential equation (PDE) and the last one for the use of texture synthesis to reconstruct damages images.