U.S.-Spain Cooperative Research: Total Variation Methods in Image Processing

这个为期两年的奖项是为了表彰美国和西班牙在基于偏微分方程的图像处理方面的合作研究。 包括加州大学洛杉矶分校的托尼·陈和斯坦福大学的吉恩·戈卢布领导的研究小组 两名西班牙研究人员安东尼奥·马奎纳和佩普·穆莱特在 西班牙瓦伦西亚大学。 研究的目的是调查以下问题 问题：全变分（TV）图像的计算技术设计 恢复，利用空间自适应性更好地恢复电视图像中的局部细节 结合非线性扩散模型和小波变换的优点， 去噪模型 该合作利用了 美国和西班牙集团。

This two-year award for US-Spain cooperative research in PDE-based image processing involves research groups headed by Tony Chan at UCLA and Gene Golub at Stanford University and by two Spanish researchers, Antonio Marquina and Pep Mulet at the University of Valencia, Spain. The objective of the research is to investigate the following problems: the design of computational techniques for total variation (TV) image restoration, the use of spatial adaptivity to better recover local details in TV image restoration, and combining the advantages of nonlinear diffusion models and wavelet denoising models. The collaboration takes advantage of the complementary expertise of the US and Spanish groups.