基于单传感器结构的压缩感知多光谱去马赛克

H. Aggarwal, A. Majumdar
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引用次数: 27

摘要

本文讨论了使用压缩传感(CS)技术从单传感器相机中恢复多光谱图像。这是一个探索性的工作,因为这个特殊的问题以前没有解决过。我们考虑了两种类型的传感器阵列-均匀和随机;Kronecker CS (KCS)和群稀疏重建两种恢复方法。进行了两组实验。从第一组实验中我们发现,对于随机抽样,KCS和群稀疏恢复都能产生良好的结果,但对于均匀抽样,只有KCS能产生良好的结果。在第二组实验中,我们将我们提出的技术与最先进的方法进行了比较。我们发现我们提出的方法产生了相当好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Compressive sensing multi-spectral demosaicing from single sensor architecture
This paper addresses the recovery of multi-spectral images from single sensor cameras using compressed sensing (CS) techniques. It is an exploratory work since this particular problem has not been addressed before. We considered two types of sensor arrays - uniform and random; and two recovery approaches - Kronecker CS (KCS) and group-sparse reconstruction. Two sets of experiments were carried out. From the first set of experiments we find that both KCS and group-sparse recovery yields good results for random sampling, but for uniform sampling only KCS yields good results. In the second set of experiments we compared our proposed techniques with state-of-the-art methods. We find that our proposed methods yields considerable better results.
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