Superresolution Videos and Optical Flow based on Combinatorial and Variational Optimization

基于组合和变分优化的超分辨率视频和光流

基本信息

批准号：
243568440
负责人：
Professor Dr.-Ing. Thomas Brox
金额：
--
依托单位：
Lehrstuhl für Informatik IX: Bildverarbeitung und Künstliche Intelligenz
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2014
资助国家：
德国
起止时间：
2013-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/243568440?language=en
关键词：
Superresolution Videos Optical Flow based

项目摘要

Humans have the capability to draw very precise information from video even in case of very bad image quality. This astonishing capability becomes evident only when we look at the single images of a video, where we find out how noisy and blurry they typically are. This is also true in the era of HD videos, which formally have a high resolution, yet due to natural limitations in recording, single frames cannot provide the same quality as photos with the same resolution. In this project, the information of successive frames of a video are sought to be combined in a way that the quality and resolution of all frames can be increased. As the central hypothesis we claim that optical flow estimation, denoising, and superresolution are coupled problems. Thus, based on extensive prior work in these areas, we will develop techniques that simultaneously compute very precise optical flow and denoised single frames at a higher resolution. Concrete subprojects are concerned with the modeling of motion blur, fast motion, and occlusions in the context of video superresolution. We believe that joint optimization of optical flow and superresolution will provide new opportunities in video analysis, it will enable the restoration of old movies, and it will allow to lift existing low resolution videos to modern HD resolution (and beyond).

即使图像质量非常糟糕，人类也可以从视频中汲取非常精确的信息。只有当我们查看视频的单个图像时，这种惊人的功能才能显而易见，在这里我们发现它们通常是多么嘈杂和模糊。在高清视频时代，正式具有很高的分辨率，但由于录制的自然限制，单帧不能提供与具有相同分辨率的照片相同的质量。在这个项目中，寻求将视频的连续帧信息组合在一起，以提高所有框架的质量和分辨率。作为中心假设，我们声称光流估计，脱氧和超分辨率是耦合问题。因此，基于这些领域的大量先前工作，我们将开发同时计算非常精确的光流并以较高分辨率的单帧的技术。具体的子标准与视频超同的背景下的运动模糊，快速运动和阻塞的建模有关。我们认为，光流和超分辨率的联合优化将在视频分析中提供新的机会，它将恢复旧电影，并且将使现有的低分辨率视频将现有的低分辨率视频提升为现代HD分辨率（及以后）。