Asian Journal of Computer Science and Technology (AJCST)
A Review Paper on Image Inpainting and their Different TechniquesAuthor : Pranjali Joshi and Neeraj Shrivastav
Volume 7 No.1 January-June 2018 pp 108-111
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 about various inpainting systems like Wavelet Transform inpainting, Exemplar based picture inpainting, PDE based picture inpainting, surface combination based picture inpainting.
Image inpainting, Image processing, Exemplar Based Inpainting, object removal, Noise, Image Reconstruction
 Jaspreet Kaur Chhabra and Vijay Birchha, “An Enhanced Technique for Exemplar based Image Inpainting”, International Journal of Computer Applications (IJCA), Vol. 115, No. 17, April 2015.
 Ankur G. Patel, Shashwat kumar and Ankit D. Prajapati, “Analysis of Exemplar Based Image Inpainting”, IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5, No. 1, pp. 800-804, 2014.
 M Bertalmio, L Vese, G Sapiro and S.Osher, “Simultaneous structure and texture image inpainting,” IEEE Transactions on Image Processing, Vol. 12, pp. 882-889, 2003.
 Jaspreet Kaur Chhabra and Mr. Vijay Birchha, “Detailed Survey on Exemplar Based Image Inpainting Techniques”, (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5, No. 5, pp. 6350-6354, 2014.
 Pritika Patel and Pritika Patel, “Review of Different Inpainting Algorithms”, International Journal of Computer Applications (IJCA) Vol. 59– No.18, December 2012.
 Rajul Suthar and Mr. Krunal R. Patel, “A Survey on Various Image Inpainting Techniques to Restore Image”, International Journal of Engineering Research and Applications, Vol. 4, No. 2, Version 1, pp. 85-88, February 2014.
 Nirali Pandya and Bhailal Limbasiya, “A Survey on Image Inpainting Techniques”, International Journal of Current Engineering and Technology, 2013.
 A Vijayalakshmi and Pethuru Raj, “Modified Exemplar based Image Inpainting Algorithm”, International Journal of Computer Applications (IJCA), Vol. 135, No. 6, February 2016.
 M. Bertalmio, G. Saprio, V. Caselles, and C. Ballester, “Image Inpainting”, Proceedings of the 27th annual conference on Computer graphics and interactive technique, pp. 417-424, 2000.
 R. Mart´ınez-Noriega, A. Roumy and G. Blanchard, “Exemplar-Based Image Inpainting: Fast Priority and Coherent Nearest Neighbor Search”, 2012 IEEE International Workshop on Machine Learning For Signal Processing, Santander, Spain, Sept. 23–26, 2012
 Dong, Bin, Hui Ji, Jia Li, Zuowei Shen, and Yuhong Xu. “Wavelet frame based blind image inpainting”, Applied and Computational Harmonic Analysis, Vol. 32, No. 2, pp. 268-279, 2012.
 Xie, Junyuan, Linli Xu, and Enhong Chen, “Image denoising and inpainting with deep neural networks”, In Advances in neural information processing systems, pp. 341-349. 2012.
 Dong, Weisheng, Guangming Shi, and Xin Li. “Nonlocal image restoration with bilateral variance estimation: a low-rank approach”, IEEE transactions on image processing, Vol. 22, No. 2, pp. 700-711, 2013.
 Hareesh, Anamandra Sai, and Venkatachalam Chandrasekaran. “Exemplar-based color image inpainting: a fractional gradient function approach”, Pattern Analysis and Applications, Vol. 17, No. 2, pp. 389-399, 2014.
 Qing Zhang and Jiajun Lin, “Exemplar-Based Image Inpainting Using Color Distribution Analysis”, Journal Of Information Science and Engineering, Vol. 28, pp. 641-654, 2012.
 Liu, Yunqiang, and Vicent Caselles, “Exemplar-based image inpainting using multiscale graph cuts”, IEEE transactions on image processing, Vol. 22, No. 5, pp. 1699-1711, 2013.