IJIGSP Vol. 11, No. 8, 8 Aug. 2019
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Patch Inpainting, Adaptive Patch Size, sequencing of the priority terms
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.
Anupama S Awati, Meenakshi. R. Patil, " Patch based Image Inpainting Technique Using Adaptive Patch Size and Sequencing of Priority Terms", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.11, No.8, pp. 60-70, 2019. DOI: 10.5815/ijigsp.2019.08.06
[1]A. Criminisi, P. Pérez, and K. Toyama. Object removal by exemplar-based inpainting. In Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition, volume 2, page 721, Los Alamitos, CA, USA, 2003. IEEE Computer Society.
[2]A. Criminisi, P. Pérez, and K. Toyama. Region filling and object removal by exemplar-based image inpainting. IEEE Trans. Image Processing, 13:1200–1212, 2004.
[3]G.Anto Silviya and V.R.Bhuma, “Exemplar-Based Image Inpainting by Laplacian Approximation Method Using Spatiogram”, International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622.
[4]Aur´elie Bugeau, Vinh-Thong Ta and Nicolas Papadakis, “Variational Exemplar-based Image Colorization”, HAL 00803219, Version-1, March-2013.
[5]Jason C. Hung, Chun-Hong Hwang, Yi-Chun Liao, Nick C. Tang and Ta-Jen Chen, “Exemplar-based Image Inpainting base on Structure Construction”, Journal Of Software, Vol. 3, No. 8, November 2008.
[6]C Guillemot, O Le Meur, “Image inpainting: Overview and recent advances”, IEEE signal processing magazine, 2014.
[7]Ding Ding , Sundaresh Ram and Jeffrey J. Rodríguez “Image Inpainting Using Nonlocal Texture Matching and Nonlinear Filtering”, IEEE Transactions On Image Processing, Vol. 28, No. 4, April 2019.
[8]Fan Qian, Zhang Lifeng, Hu Xuelong, “Exemplar-based image inpainting algorithm using adaptive sample and candidate patch system”, 2015 IEEE 12th Interational Conference on Electronic Measurement & Instruments ICEMI'2015.
[9]Olivier Le Meur, Josselin Gautier Christine Guillemot, “Examplar-Based Inpainting Based On Local Geometry”, Image Processing (ICIP), 2011 ieeexplore.ieee.org.
[10]R. Martinez-Noriega, A. Roumy G. Blanchard, “Exemplar·Based Image Inpainting: Fast Priority And Coherent Nearest Neighbor Search”, 2012 IEEE International Workshop On Machine Learning For Signal Processing, SEPT. 23-26, 2012
[11]LIU Ying, LIU Chan-juan, ZOU Hai-lin, ZHOU Shu-sen, SHEN Qian, “A Novel Exemplar-based Image Inpainting Algorithm”, International Conference on Intelligent Networking and Collaborative Systems IEEE computer society.
[12]Kaushik kumar R. Patel, Lalit Jain, “A Novel Approach to Exemplar Based Image Inpainting”, IEEE Technology for Humanity.
[13]Zongben Xu and Jian Sun Image Inpainting by Patch Propagation Using Patch Sparsity IEEE Transactions On Image Processing, Vol. 19, No. 5, May 2010 1153.
[14]A patch-based image inpainting based on structure consistence Hui-Yu Huang Department of Computer Science and Information Engineering, National Formosa University 64, Wun-Hua Rd., Huwei, Yunlin 632, Taiwan E-mail: hyhuang@nfu.edu.tw Chun-Nan Hsiao 2010 IEEE
[15]2011 4th International Congress on Image and Signal Processing An improved scheme for Criminisi’s inpainting algorithm Song Zhang, Xuya Zhou 2011 IEEE
[16]Bi-Layer Inpainting For Novel View Synthesis Hwasup Lim, Yong Sun Kim, Seungkyu Lee, Ouk Choi, James D. K. Kim, and Changyeong Ki 2011 18th IEEE International Conference on Image Processing
[17]Proceedings of the 2012 Interational Conference on Machine Learing and Cybernetics, Xian, 15-17 July, 2012 Fast Exemplar-Based Image Inpainting Approach Hui-Qin Wang1, Qing Cheni, Cheng-Hsiung Hsieh2>, Peng yul 2012 IEEE
[18]IEEE Transactions On Image Processing, VOL. 25, NO. 1, JANUARY 2016 249 Multi-Scale Patch-Based Image Restoration Vardan Papyan and Michael Elad,
[19]IEEE Transactions On Image Processing, VOL. 24, NO. 1, JANUARY 2015 Context-Aware Patch-Based Image Inpainting Using Markov Random Field Modeling Tijana Ruži´ c and Aleksandra Pižurica,
[20]Sarawut Akinori Nishihara, “Exemplar-Based Image Inpainting With Patch Shifting Scheme”.
[21]Ding Ding , Sundaresh Ram and Jeffrey J. Rodríguez “Image Inpainting Using Nonlocal Texture Matching and Nonlinear Filtering”, IEEE Transactions On Image Processing, Vol. 28, No. 4, April 2019.
[22]Deng L-J, Huang T-Z, Zhao X-L (2015) “Exemplar-Based Image Inpainting Using a Modified Priority Definition”. PLoS ONE 10(10): e0141199. doi:10.1371/journal.pone.0141199
[23]Song Wang Hong Li Xia Zhu Ping Li, “An Evaluation Index Based on Parameter Weight for Image Inpainting Quality”2008 IEEE computer society.
[24]“Inpainting with Refinement of Vicinity Patches using alpha trim filter for Heritage Sites” in International Journal of Current Engineering and Technology E ISSN 2277–4106, P ISSN 2347 5161©2019 INPRESSCO Vol.9, No.2 (March/April 2019).
[25]Inpainting of Structural Reconstruction of Monuments Using Singular Value Decomposition Refinement of Patches", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.11, No.5, pp. 44-53, 2019.DOI: 10.5815/ijigsp.2019.05.05, in MECS (http://www.mecs-press.org/).
[26]Image Inpainting using exemplar based technique with improvised data term CTEMS 2018, K.L.S. Gogte Institute of Technology, Belagavi, Dec 2018.