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Journal articles on the topic 'Exemplar Based Inpainting'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Haridas, Arsha, and Shubham Agrawal. "Exemplar Method Based Image Inpainting." International Journal of Scientific Engineering and Research 4, no. 4 (2016): 59–62. https://doi.org/10.70729/ijser15759.

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2

A, Ankitha. "Exemplar Based Image Inpainting." IOSR journal of VLSI and Signal Processing 4, no. 2 (2014): 13–16. http://dx.doi.org/10.9790/4200-04221316.

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3

Et. al., Shweta Dhondse. "Intuitionistic Fuzzy Sets Based Inpainting for Reconstruction of Heritage Images." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 5556–65. http://dx.doi.org/10.17762/turcomat.v12i3.2219.

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Image inpainting is a process of reconstructing damaged or missing part of an image. Initially the work of restoration was performed by skilled artists and was limited to paintings and other artwork of eminence but this process was very tedious and strenuous and therefore digital image inpainting was introduced. The application of inpainting in reconstruction of heritage images is garnering a lot of attention from researchers. The reconstruction of heritage images using inpainting poses a challenging task because of its very high resolution and high meaning full structure content. In tradition

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Cao, Frédéric, Yann Gousseau, Simon Masnou, and Patrick Pérez. "Geometrically Guided Exemplar-Based Inpainting." SIAM Journal on Imaging Sciences 4, no. 4 (2011): 1143–79. http://dx.doi.org/10.1137/110823572.

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5

Amol, Pawar, and A.P. Phatale Prof. "A EFFECTIVE WAY TO MODIFY VIDEO FOR DELETING FORGROUND OBJECT FROM BACKGROUND USING EXEMPLAR BASED INPAINTING METHOD." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 3 (2016): 346–56. https://doi.org/10.5281/zenodo.47048.

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A surveillance video for analyzing doubtful action in CCTV footage can be observed by military, police, Intelligance Bureau daily but some footage must be kept private and it’s content not getting viral for maintaining peace in society for this purpose reconstructing that footage is good option to avoid any misuse with that footage so we have implemented inpainting method to modify that video for deleting forground object from background , here we have use Exemplar based inpainting method which is used in Image Inpainting this method is combination of PDE based and Texture Synthesis base

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6

Fan, Qian, Lifeng Zhang, and Seiichi Serikawa. "Improvement of Patch Selection in Exemplar-based Image Inpainting." Journal of the Institute of Industrial Applications Engineers 3, no. 4 (2015): 197–202. http://dx.doi.org/10.12792/jiiae.3.197.

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7

Huang, Weijie, and Guoshan Zhang. "Improvement of the exemplar-based inpainting." Journal of Electronic Imaging 25, no. 5 (2016): 053038. http://dx.doi.org/10.1117/1.jei.25.5.053038.

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8

A., Vijayalakshmi, and Pethuru Raj. "Modified Exemplar based Image Inpainting Algorithm." International Journal of Computer Applications 135, no. 6 (2016): 24–28. http://dx.doi.org/10.5120/ijca2016908577.

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9

Yu, Shu Chun, Xiao Yang Yu, Jian Ying Fan, Hai Bin Wu, Yang Wang, and Qiao Hua Feng. "Disparity Image Inpainting with Improved Method Based on Exemplar." Applied Mechanics and Materials 121-126 (October 2011): 4431–35. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.4431.

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To combat the problems of disparity image inpainting, an improved exemplar-based image inpainting method is proposed. The original stereo image we select which corresponds to disparity image is decomposed by TV-based decomposition and the structural information is obtained. The patch priority in the position corresponding to the disparity image is calculated by using the structural information, which reflects true characteristics of the original stereo image and disparity image. Experimental results show that inpainting performance is better with the guidance of this patch priority for dispari

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10

Zhao, Junhong, Jintao Tan, Yaobin Huang, and Chuanlong Lu. "Improved image inpainting exemplar-based algorithms by boundary priori-knowledge." MATEC Web of Conferences 355 (2022): 03004. http://dx.doi.org/10.1051/matecconf/202235503004.

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Image inpainting plays an important role in restoration of cultural relics, pictures beautification. Criminisi algorithm creates good results in large-area inpainting. However, it does still have some deficiencies such as over-extending. In this paper, two improved algorithms based on prior knowledge of the boundary had been proposed by simulating the idea of manual repairing. An algorithm, by simulating the strategy that the next inpainted pixel will be near to the prior one, named nearer neighbor first algorithm, can void the random bounding of the to-be-inpainted pixle. Another algorithm, b

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11

I. J., Sreelakshmy, and Binsu C. Kovoor. "A Hybrid Inpainting Model Combining Diffusion and Enhanced Exemplar Methods." Journal of Data and Information Quality 13, no. 3 (2021): 1–19. http://dx.doi.org/10.1145/3418035.

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Image inpainting is a technique in the world of image editing where missing portions of the image are estimated and filled with the help of available or external information. In the proposed model, a novel hybrid inpainting algorithm is implemented, which adds the benefits of a diffusion-based inpainting method to an enhanced exemplar algorithm. The structure part of the image is dealt with a diffusion-based method, followed by applying an adaptive patch size–based exemplar inpainting. Due to its hybrid nature, the proposed model exceeds the quality of output obtained by applying conventional

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12

Suma N and Dr. Kusuma Kumari B.M. "Understanding Image Inpainting." International Research Journal on Advanced Engineering and Management (IRJAEM) 3, no. 02 (2025): 319–22. https://doi.org/10.47392/irjaem.2025.0050.

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Image inpainting is a computer vision technique that aims to fill in missing or damaged areas of an image with plausible content. The goal is to create a visually coherent and realistic image that seamlessly integrates the inpainted regions with the surrounding context. Image inpainting techniques typically utilize nearby information or context to infer the missing or damaged pixels. They can be broadly classified into two categories: exemplar-based inpainting methods and partial differential equation-based inpainting methods. Exemplar-based inpainting methods rely on the idea of finding simil

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13

U.Gaikwad, Vaishali, and P. V. kulkarni. "Exemplar-based Video Inpainting for Occluded Objects." International Journal of Computer Applications 81, no. 13 (2013): 28–30. http://dx.doi.org/10.5120/14075-2419.

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14

Koochari, Abbas, and Mohsen Soryani. "Exemplar-based video inpainting with large patches." Journal of Zhejiang University SCIENCE C 11, no. 4 (2010): 270–77. http://dx.doi.org/10.1631/jzus.c0910308.

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15

Alilou, Vahid K., and Farzin Yaghmaee. "Fast Exemplar-Based Image Inpainting Using a New Pruning Technique." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 10 (2017): 1754019. http://dx.doi.org/10.1142/s0218001417540192.

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This paper presents a new algorithm for fast exemplar-based image inpainting by using image pyramid and a novel pruning scheme. The proposed technique separates the inpainting process into three major steps. First the model determines which patch belonging to the inpainting region should be filled first. Then the pruning system analyzes the selected patch and weeds out regions having no chance to be the best matching patch. Finally, it performs a fast texture synthesis based on greedy search method in the remaining regions to fill the selected patch. Compared with previous methods, the propose

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16

P, Jini. "Image Inpainting Using Image Interpolation - An Analysis." Revista Gestão Inovação e Tecnologias 11, no. 2 (2021): 1906–20. http://dx.doi.org/10.47059/revistageintec.v11i2.1807.

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Image inpainting is a computer technique of filling lost regions of an image by using available information from the surrounding area. This digital image inpainting technique has wider applications like image restoration, dis-occlusion and image/video compression. The traditional image inpainting approaches Partial Differential Equation (PDE) based method and Exemplar based method mainly focus on the size of the target region to be filled. PDE is a pixel oriented method and works well if the region to be filled is small. On the other hand exemplar based method is a patch based method and works

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17

Joshi, Pranjali, and Neeraj Shrivastav. "A Review Paper on Image Inpainting and their Different Techniques." Asian Journal of Computer Science and Technology 7, no. 1 (2018): 108–11. http://dx.doi.org/10.51983/ajcst-2018.7.1.1821.

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Image Inpainting is an art of modifying the digital image in such a way that the modifications are undetectable to an observer who has no idea about the original image. The essential thought behind the system is to consequently fill in lost or missing parts of a picture utilizing data from the encompassing region. It is utilized for rebuilding of old movies and protest expulsion in computerized photos. Different calculations have introduced in the past to accomplish the undertaking of picture inpainting. In this paper we give a survey of various systems utilized for picture Inpainting. We talk

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18

Prasanthi, Tammineni Shanmukha, Swarajya Madhuri Rayavarapu, Yenneti Laxmi Lavanya, et al. "Performance Analysis of Different Applications of Image Inpainting Based on Exemplar Technique." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 4 (2023): 113–17. http://dx.doi.org/10.17762/ijritcc.v11i4.6393.

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In this age of rapidly developing image processing, inpainting has been a popular and practical art. Researchers have paid considerable attention to image inpainting throughout the years due to its enormous significance and effectiveness in a wide range of image processing applications, including the removal of scratches, the elimination of objects, and the modification of faces. It is one of the most challenging issues in image processing, demanding a comprehensive understanding of the image's texture and structure. The quality of inpainted image is a crucial factor which determines how close

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19

KaurChhabra, Jaspreet, and Vijay Birchha. "An Enhanced Technique for Exemplar based Image Inpainting." International Journal of Computer Applications 115, no. 17 (2015): 20–25. http://dx.doi.org/10.5120/20242-2595.

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20

Kim, Jin-Ju, and Si-Woong Lee. "Effective Exemplar-Based Image Inpainting Using Patch Extrapolation." Journal of the Korea Contents Association 14, no. 2 (2014): 1–9. http://dx.doi.org/10.5392/jkca.2014.14.02.001.

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21

Patel, Jayesh, and Tanuja K. Sarode. "Exemplar based Image Inpainting with Reduced Search Region." International Journal of Computer Applications 92, no. 12 (2014): 27–33. http://dx.doi.org/10.5120/16063-5295.

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22

G.Patel, Ankur, Shashwat Kumar, and Ankit D. Prajapati. "Improved Exemplar based Image Inpainting using Structure Tensor." International Journal of Computer Applications 96, no. 15 (2014): 9–14. http://dx.doi.org/10.5120/16868-6763.

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23

G.Patel, Ankur, Ankit D. Prajapati, and Pritika H. Patel. "Improved Robust Algorithm for Exemplar based Image Inpainting." International Journal of Computer Applications 101, no. 6 (2014): 23–27. http://dx.doi.org/10.5120/17692-8659.

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24

Kim, Bosung, and Jong-Seung Park. "Exemplar-Based Image Inpainting for Spherical Panoramic Image." Journal of KIISE 43, no. 4 (2016): 437–49. http://dx.doi.org/10.5626/jok.2016.43.4.437.

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25

Zhang, Lei, Baosheng Kang, Benting Liu, and Fei Zhang. "Image Inpainting Based on Exemplar and Sparse Representation." International Journal of Signal Processing, Image Processing and Pattern Recognition 9, no. 9 (2016): 177–88. http://dx.doi.org/10.14257/ijsip.2016.9.9.17.

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26

Liu, Huaming, Guanming Lu, Xuehui Bi, and Weilan Wang. "Hierarchical Guidance Strategy and Exemplar-Based Image Inpainting." Information 9, no. 4 (2018): 96. http://dx.doi.org/10.3390/info9040096.

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27

Lee, Jino, Dong-Kyu Lee, and Rae-Hong Park. "Robust exemplar-based inpainting algorithm using region segmentation." IEEE Transactions on Consumer Electronics 58, no. 2 (2012): 553–61. http://dx.doi.org/10.1109/tce.2012.6227460.

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28

Kim, Baek-Sop, JunSeong Kim, and Jaehwa Park. "Exemplar based inpainting in a multi-scaled space." Optik 126, no. 23 (2015): 3978–81. http://dx.doi.org/10.1016/j.ijleo.2015.07.168.

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29

Arias, Pablo, Gabriele Facciolo, Vicent Caselles, and Guillermo Sapiro. "A Variational Framework for Exemplar-Based Image Inpainting." International Journal of Computer Vision 93, no. 3 (2011): 319–47. http://dx.doi.org/10.1007/s11263-010-0418-7.

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30

Yunqiang Liu and V. Caselles. "Exemplar-Based Image Inpainting Using Multiscale Graph Cuts." IEEE Transactions on Image Processing 22, no. 5 (2013): 1699–711. http://dx.doi.org/10.1109/tip.2012.2218828.

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31

Ahmed, Mariwan Wahid, and Alan Anwer Abdulla. "Quality Improvement for Exemplar-based Image Inpainting using a Modified Searching Mechanism." UHD Journal of Science and Technology 4, no. 1 (2020): 1. http://dx.doi.org/10.21928/uhdjst.v4n1y2020.pp1-8.

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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 importan

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32

Guo, H. R., and W. H. Wang. "A fast image inpainting algorithm based on an adaptive scanning strategy." EAI Endorsed Transactions on e-Learning 8, no. 4 (2023): e1. http://dx.doi.org/10.4108/eetel.3141.

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OBJECTIVES: In exemplar-based image inpainting algorithms, there are often issues with the calculation of patch similarity for matching, suboptimal strategies for selecting matching patches, and low inpainting speed.METHODS: This paper first uses the variable scale cross-scan block line progressive scan to solve the problem of slow scanning speed and invalid priority formula. Then, an improved weight similarity formula is used for searching to solve the problem of poor computing strategy for similar matching patches. The search range of matching patches gradually increases from small to large

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33

Rao, Janardhana, K. Revathi, Yalamanchili Bhanusree, Venkata Krishna Odugu, and Harish Babu Gade. "Development of Image Inpainting for object removal using Enhanced Patch Priority and Matching Measures." E3S Web of Conferences 472 (2024): 02010. http://dx.doi.org/10.1051/e3sconf/202447202010.

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Image inpainting can be used to fix broken images and get rid of distracting elements. In exemplar based methods, patch priority computation and exemplar patch selection are crucial to the success of image inpainting technique. The dropping effect occurred in the highest patch priority computation and matching error in the best patch selection are the major issues in the exemplar inpaint methods. In this paper, the enhanced priority calculation technique is employed to avoid the dropping effect and introduced the new similarity measuring process, Mean Squared Error (MSD). The efficacy of the p

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34

Wang, Wenzhen, Na Deng, Binjie Xin, Chi-wai Kan, Yiliang Wang, and Shuaigang Lu. "Research on texture image inpainting of jacquard fabric based on non-single vision." Textile Research Journal 90, no. 13-14 (2019): 1462–76. http://dx.doi.org/10.1177/0040517519892924.

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For the texture image inpainting of jacquard fabric with a large damaged region but complete data information around it, traditional exemplar-based image inpainting algorithms are not only have rapid falling traditional confidence value, but also the matching precision is greatly limited due to the lack of robustness, which results in a wrong guided direction and an unsatisfactory inpainting effect. To solve the above-mentioned problems, a novel digital image acquisition system for damaged fabric was designed and one set of texture image inpainting algorithms of jacquard fabric based on non-si

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35

Zhang xiaona, Qi Guoqing, and Wang qiang. "Blotches Restoration on Exemplar-based Image Inpainting in Archived." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 4, no. 17 (2012): 388–96. http://dx.doi.org/10.4156/aiss.vol4.issue17.45.

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36

LU, Xiao-bao, and Wei-lan WANG. "Improved exemplar-based inpainting algorithm for broken Thangka images." Journal of Computer Applications 30, no. 4 (2010): 943–46. http://dx.doi.org/10.3724/sp.j.1087.2010.00943.

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37

Lu Wenxia, 卢雯霞, and 何凯 He Kai. "Exemplar-Based Inpainting Algorithm with Rotation and Scaling Transformation." Laser & Optoelectronics Progress 55, no. 3 (2018): 031006. http://dx.doi.org/10.3788/lop55.031006.

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38

Aujol, Jean-François, Saïd Ladjal, and Simon Masnou. "Exemplar-Based Inpainting from a Variational Point of View." SIAM Journal on Mathematical Analysis 42, no. 3 (2010): 1246–85. http://dx.doi.org/10.1137/080743883.

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39

Wang, Haixia, Li Jiang, Ronghua Liang, and Xiao-Xin Li. "Exemplar-based image inpainting using structure consistent patch matching." Neurocomputing 269 (December 2017): 90–96. http://dx.doi.org/10.1016/j.neucom.2016.08.149.

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40

Deng, Liang-Jian, Ting-Zhu Huang, and Xi-Le Zhao. "Exemplar-Based Image Inpainting Using a Modified Priority Definition." PLOS ONE 10, no. 10 (2015): e0141199. http://dx.doi.org/10.1371/journal.pone.0141199.

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41

Zhou, Yatong, Lin Li, and Kewen Xia. "Research on weighted priority of exemplar-based image inpainting." Journal of Electronics (China) 29, no. 1-2 (2012): 166–70. http://dx.doi.org/10.1007/s11767-012-0843-6.

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42

Prasanthi, Tammineni Shanmukha, Swarajya Madhuri Rayavarapu, Yenneti Laxmi Lavanya, Gottapu Santosh Kumar, and Gottapu Sasibhushana Rao. "Investigation of Optimal Image Inpainting Techniques for Image Reconstruction and Image Restoration Applications." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 6s (2023): 271–76. http://dx.doi.org/10.17762/ijritcc.v11i6s.6918.

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People in today's society take a lot of pictures with their smartphones and also make an effort to keep their old photographs safe, but with time, those photographs deteriorate. Image inpainting is the art of reconstructing damaged or missing parts of an image. Repairing scratches in photographs or film negatives, or adding or removing elements like stamped dates or "red-eye," are all possible through inpainting. In order to restore the image many techniques have been developed, significant techniques include exemplar based inpainting, coherent based inpainting and method for correction of non

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43

Abdulla, Alan Anwer, and Mariwan Wahid Ahmed. "An improved image quality algorithm for exemplar-based image inpainting." Multimedia Tools and Applications 80, no. 9 (2021): 13143–56. http://dx.doi.org/10.1007/s11042-020-10414-6.

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44

Byongsu, Hwang, Jo Jonghyon, and Ri Cholsu. "AN IMPROVED EXEMPLAR-BASED IMAGE INPAINTING ALGORITHM FOR ERROR CONCEALMENT." ICTACT Journal on Image and Video Processing 8, no. 1 (2017): 1583–87. http://dx.doi.org/10.21917/ijivp.2017.0223.

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45

PARK, Jinki, Jaehwa PARK, Young-Bin KWON, Chan-Gun LEE, and Ho-Hyun PARK. "Exemplar-Based Inpainting Driven by Feature Vectors and Region Segmentation." IEICE Transactions on Information and Systems E98.D, no. 4 (2015): 972–75. http://dx.doi.org/10.1587/transinf.2014edl8201.

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46

Arias, P., V. Caselles, and G. Facciolo. "Analysis of a Variational Framework for Exemplar-Based Image Inpainting." Multiscale Modeling & Simulation 10, no. 2 (2012): 473–514. http://dx.doi.org/10.1137/110848281.

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47

Wang, Jing, Ke Lu, Daru Pan, Ning He, and Bing-kun Bao. "Robust object removal with an exemplar-based image inpainting approach." Neurocomputing 123 (January 2014): 150–55. http://dx.doi.org/10.1016/j.neucom.2013.06.022.

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48

Reshniak, Viktor, Jeremy Trageser, and Clayton G. Webster. "A Nonlocal Feature-Driven Exemplar-Based Approach for Image Inpainting." SIAM Journal on Imaging Sciences 13, no. 4 (2020): 2140–68. http://dx.doi.org/10.1137/20m1317864.

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49

Criminisi, A., P. Perez, and K. Toyama. "Region Filling and Object Removal by Exemplar-Based Image Inpainting." IEEE Transactions on Image Processing 13, no. 9 (2004): 1200–1212. http://dx.doi.org/10.1109/tip.2004.833105.

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50

D, Devasruthi, Hema P. Menon, and K. A. Narayanankutty. "FEBEMD and Exemplar based Hybrid Image Inpainting for Occlusion Removal." International Journal of Computer Applications 28, no. 8 (2011): 38–44. http://dx.doi.org/10.5120/3405-4749.

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