科学研究
报告题目:

Fourier Masked Phase Retrieval:Mask Design, Blind Recovery, and Sparsity Modeling

报告人:

常慧宾 研究员(天津师范大学)

报告时间:

报告地点:

腾讯会议ID:914-957-139

报告摘要:

Phase retrieval plays an important role in vast industrial and scientific applications, which is essentially a non-convex and possible non-smooth optimization problem mathematically. As a special and important case, recovery from Fourier masked measurements is critical for practical imaging including x-ray imaging, material sciences, and optics. In this talk, we mainly concern how to design masks for unique recovery, jointly reconstruct the mask and sample, and design fast convergent splitting algorithm with sparsity modeling.

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