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Incomplete Image Completion through GAN

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摘要 There are two difficult in the existing image restoration methods.One is that the method is difficult to repair the image with a large damaged,the other is the result of image completion is not good and the speed is slow.With the development and application of deep learning,the image repair algorithm based on generative adversarial networks can repair images by simulating the distribution of data.In the process of image completion,the first step is trained the generator to simulate data distribution and generate samples.Then a large number of falsified images are quickly generated using the generative adversarial network and search for the code of the closest damaged image.Finally,the generator generates missing content by using this code.On this basis,this paper combines the semantic loss function and the perceptual loss function.Experimental result show that the method successfully predicts the information of large areas missing in the image,and realizes the photorealism,producing clearer and more consistent results than previous methods.
出处 《Journal of Quantum Computing》 2021年第3期119-126,共8页 量子计算杂志(英文)
基金 supported by Scientific Research Starting Project of SWPU(No.0202002131604) Major Science and Technology Project of Sichuan Province(No.8ZDZX0143) Ministry of Education Collaborative Education Project of China(No.952) Fundamental Research Project(Nos.549,550).
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  • 1王树根,郑精灵.基于纹理匹配的影像缺损信息填充方法[J].测绘通报,2004(12):21-23. 被引量:11
  • 2Bertalmio M,Sapiro G,Caselles V,et al.Image inpainting[A].In:Proceedings of International Conference on Computer Graphics and Interactive Techniques[C],New Orleans,Louisiana,USA,2000:417 -424.
  • 3Chan T F,Shen J H.Non-texture inpainting by curvature-driven diffusions (CDD)[J].Journal of Visual Communication and Image Representation,2001,12(4):436 -449.
  • 4Chan T F,Shen J H.Mathematical models for local non-texture inpainting[J].SIAM Journal of Applied Mathematics,2001,62(3):1019 -1043.
  • 5Chan T F,Kang S H,Shen J H.Euler's elastica and curvature based inpainting[J].SIAM Journal of Applied Mathematics,2002,63 (2):564 - 592.
  • 6Tsai A,Yezzi J A,Willsky A S.Curve evolution implementation of the Mumford-Shah functional for image segmentation,denoising,interpolation and magnification[J].IEEE Transactions on Image Processing,2001,10(8):1169 - 1186.
  • 7Esedoglu S,Shen J H.Digital inpainting based on the Mumford-Shah-Euler image model[J].European Journal on Applied Mathematics,2002,13(4):353 - 370.
  • 8Bertalmio M,Vese L,Sapiro G,et al.Simultaneous texture and structure image inpainting[J].IEEE Transactions on Image Processing,2003,12 (8):882 - 889.
  • 9Efros A A,Leung T K.Texture synthesis by non-parametric sampling[A].In:Proceedings of the IEEE Computer Society International Conference on Computer Vision[C],Washington DC,USA,1999,2:1033 - 1038.
  • 10Harald G.A combined PDE and texture synthesis approach to inpainting[A].In:Proceedings of 8th European Conference on Computer Vision[C],Prague,Czech Republic,2004,2:214 -224.

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