US-Netherlands Cooperative Research: Fast Methods for ImageSequence Identification and Restoration

美国-荷兰合作研究：图像序列识别和恢复的快速方法

• 批准号: 8814578
• 负责人: Howard Kaufman
• 金额: $ 1.12万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-03-01 至 1993-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8814578&HistoricalAwards=false
• 关键词: US; Netherlands; Cooperative; Research; Fast

This award supports Professors Howard Kaufman and John W. Woods of Rensselaer Polytechnic Institute to collaborate in research in computer image processing with Professor Jan Biemond of the Department of Electrical Engineering of the Delft University of Technology, The Netherlands. The objective of their collaboration is to evaluate various image sequence restoration techniques in terms of their effectiveness and efficiency on different parallel computer architectures. In particular, Professor Biemond will use iterative based procedures and an AP500 array processor, while Professors Kaufman and Woods will use recursive based procedures and a Sequent Balance 8000 multiprocessor system. Identification of the spatial and temporal image dynamics will be considered by both investigators. Another important aspect of the cooperative research will be in algorithm design. It is important that a good cross-section of procedures be used to give all processors the chance to perform in their own domains. At the same time, the methods of implementation have to be closely analyzed to make sure that the measurements on the architecture's power are fair. The area of fast restoration of distorted image sequences is one of growing importance, for which effective techniques are needed. Real-time image enhancement is becoming increasingly more feasible due to recent hardware advances, such as DSP chips and parallel architectures. Image restoration is usually more computationally intensive and is more difficult to achieve at high speeds. The goals of this collaboration are ambitious, but the expected result of meaningful comparisons of different methodologies will be very worthwhile.

该奖项支持教授霍华德考夫曼和约翰W。树林 Rensselaer Polytechnic Institute合作研究 计算机图像处理与教授扬Biemond的 德国德尔夫特大学电气工程系 技术，荷兰。 他们合作的目的 是评估各种图像序列恢复技术， 在不同的平行领域的效力和效率 计算机体系结构 特别是，比蒙德教授将使用 基于迭代的程序和AP 500阵列处理器，而 考夫曼教授和伍兹教授将使用基于递归的程序 和Sequent Balance 8000多处理器系统。 识别 的空间和时间的图像动态将被认为是由 两位调查员 合作社的另一个重要方面是 研究将在算法设计。 重要的是， 程序的横截面被用来给所有处理器， 有机会在自己的领域中表演。 同时对 必须仔细分析实施方法，以确保 对架构功率的测量是公平的。 失真图像序列的快速恢复领域是 重要性日益增加，需要有效的技术。 实时图像增强变得越来越可行 由于最近的硬件进步，如DSP芯片和并行 建筑 图像恢复通常计算量更大 这是密集的，并且更难以在高速下实现。 的 这项合作的目标是雄心勃勃的，但预期结果 对不同方法的有意义的比较将非常 worthwhile.