多模光纤
计算机科学
稳健性(进化)
平滑度
约束(计算机辅助设计)
计算机视觉
秩(图论)
图像质量
人工智能
图像(数学)
数学
光纤
电信
生物化学
基因
组合数学
数学分析
化学
几何学
作者
Dongyue Yang,Min Hao,Guohua Wu,Chang Chen,Bin Luo,Longfei Yin
标识
DOI:10.1016/j.optlaseng.2021.106827
摘要
We present a novel scheme of single multimode fiber imaging by exploiting low-rank constraint for a faithful image recovery. Compared with the commonly-adopted sparsity constraint, the proposed scheme takes the advantage of the self-similarity property of natural images, and is demonstrated to achieve higher image quality and smoothness in multimode fiber imaging, especially in the under-sampling cases. We also demonstrate the robustness of this method to recover different kind of images against fiber bending, and discuss the low-rank parameter tunning for a stable recovery. Our findings may pave the way for a simpler and more robust scheme of single multimode fiber imaging, which could be applied for many demanding imaging tasks.
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