Image and Video Inpainting

图像和视频修复

• 批准号: 0429037
• 负责人: Guillermo Sapiro
• 金额: --
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-15 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0429037&HistoricalAwards=false
• 关键词: Image; Video; Inpainting

This project addresses the area of image and video inpainting, the technique of modifying an image in an undetectable form. The goals and applications of inpainting, which is as ancient as art itself, are numerous, from the restoration of damaged paintings and photographs to the removal of selected objects in a scene and the discovery of data behind occlusions. Image inpainting is also important for less-conventional applications such as wireless transmission and compression and image integration from camera arrays. The goal of this project is to develop a working solution to image, video, three dimensional, and multiple views inpainting and to address applications such as image and film restoration and alteration, image recovery from camera arrays, and filling-in of holes in 3D range data. Biological aspects of inpainting, through its fascinating possible connections with camouflage and the filling-in of the human blind spot, are investigated as well. The theory and applications of this project cover very diverse areas such as image processing, partial differential equations and fluid dynamics, numerical analysis, art, computer graphics, entertainment, and biology.The inpainting problem is addressed as the computation of a smooth continuation of the available spatial andtemporal information surrounding the region to be filled-in. This is achieved via partial differential equations, which incorporate principles ranging from fluid dynamics to Gestalt's smooth boundary continuation. The combination of these techniques with more classical texture synthesis algorithms is also addressed and exploited in this project. The research addresses the problem in its generality, assuming diverse and large regions to be inpainted, and derives both fundamental theoretical aspects and practicalworking systems.

这个项目涉及图像和视频修复领域，即以不可检测的形式修改图像的技术。修复的目标和应用和艺术本身一样古老，从修复受损的绘画和照片到移除场景中选定的对象和发现遮挡背后的数据，不一而足。图像修复对于非常规应用也很重要，例如无线传输和压缩以及来自摄像机阵列的图像集成。该项目的目标是开发一种用于图像、视频、三维和多视图修复的工作解决方案，并解决诸如图像和胶片恢复和更改、从相机阵列恢复图像以及填充3D距离数据中的孔洞等应用。修复的生物学方面，通过它与伪装和填补人类盲点的有趣的可能联系，也被研究。该项目的理论和应用涵盖了图像处理、偏微分方程和流体力学、数值分析、艺术、计算机图形学、娱乐和生物学等多个领域。修复问题是指对待填充区域周围的可用时空信息进行平滑连续的计算。这是通过偏微分方程组实现的，其中包含了从流体动力学到格式塔光滑边界延拓的各种原理。将这些技术与更经典的纹理合成算法相结合，也在本项目中得到了研究和开发。这项研究从一般意义上解决了这一问题，假设了不同的和大范围的区域，并得出了基本的理论方面和实际的工作体系。