SBIR Phase I: Breaking the Barriers to the Commercialization of Super-Resolution Video Enhancement Algorithms

SBIR第一期：打破超分辨率视频增强算法商业化障碍

• 批准号: 0232274
• 负责人: Richard Schultz
• 金额: $ 8.4万
• 依托单位: Machine Visionaries
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-01-01 至 2003-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0232274&HistoricalAwards=false
• 关键词: SBIR; Phase; Breaking; Barriers; Commercialization

This Small Business Innovation Research (SBIR) Phase I project will investigate the two primary barriers to the commercialization of super-resolution video enhancement, namely, that (1) the motion compensation-based video enhancement algorithms are extremely computationally-intensive, and (2) the ability to extract additional visual information from digital video is highly dependent on image sequence content. Provided that people, objects, and entire scenes move in subpixel increments between video frames or fields, this motion can be exploited by temporally integrating neighboring pictures to increase spatial resolution and to actually see details where there were once blocky pixels. The proposed research focuses on determining the feasibility of significantly increasing the processing speed of the associated numerical algorithms on desktop and notebook personal computers running Microsoft Windows or Linux, as well as determining the feasibility of automatically detecting the video frames/fields which contribute additional information to a specific region-of-interest selected for enhancement.A number of commercial applications in forensic image analysis for law enforcement and security end-users can be developed around this technology. Super resolution video enhancement is of particular interest to government agencies, such as the Department of Defense and the Department of Justice for extracting additional details from reconnaissance and surveillance video, as well as to the private sector for forensic image analysis in law enforcement, surveillance, and security. By successfully tackling the proposed technical objectives, the capability will be developed to embed super-resolution enhancement video technology into commercial nonlinear video editing software packages such as Adobe Premiere.

这个小型企业创新研究(SBIR)第一阶段项目将调查超分辨率视频增强商业化的两个主要障碍，即(1)基于运动补偿的视频增强算法计算非常密集，(2)从数字视频中提取额外视觉信息的能力高度依赖于图像序列内容。如果人、物体和整个场景在视频帧或场之间以亚像素增量移动，则可以通过对相邻图片进行时间整合来利用这种运动，以提高空间分辨率并实际查看曾经存在块状像素的细节。拟议的研究重点是确定在运行Microsoft Windows或Linux的台式机和笔记本电脑上显著提高相关数值算法处理速度的可行性，以及确定自动检测视频帧/场的可行性，这些视频帧/场为选择进行增强的特定感兴趣区域贡献了额外信息。围绕这项技术，可以开发出许多针对执法和安全最终用户的法医图像分析商业应用。超分辨率视频增强对国防部和司法部等政府机构特别感兴趣，因为它们从侦察和监控视频中提取更多细节，以及私营部门在执法、监控和安全方面进行法医图像分析。通过成功实现拟议的技术目标，将开发将超分辨率增强视频技术嵌入Adobe Premiere等商业非线性视频编辑软件包的能力。