相位恢复
带限幅
傅里叶变换
计算机科学
独特性
相(物质)
趋同(经济学)
对象(语法)
图像(数学)
反问题
算法
计算机视觉
数学优化
人工智能
数学
物理
数学分析
经济
量子力学
经济增长
作者
Xiao Kang,Xinyi Kong,Zhongyang Wang
摘要
Phase retrieval is a long-standing issue in imaging science; however, it always faces the problems of uniqueness and algorithm stagnation. Current methods to solve such problems rely heavily on support from prior information of the imaged object. In this paper, we propose an imaging method that leverages a bandlimited image and its Fourier transformed constraints for unique phase retrieval. This method can remove both trivial and nontrivial ambiguities by using the inherent constraints of the imaging system itself—without relying on prior information of the object. Furthermore, the proposed method has also been shown to succeed in special cases, including symmetric and pure phase objects. Improvement of convergence achieved by our approach is supported by numerical simulations.
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