分布式光场压缩感知

Rui Lei, Wei Shen, Zhijiang Zhang, Ying Zhou
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引用次数: 1

摘要

光场相机阵列可以看作是分布式光源。由相机阵列捕获的图像序列包含相互关联和内部相关。为了利用相关性,建立了光场与分布式压缩感知相结合的联合稀疏度模型,并针对该模型提出了一种恢复算法——同步正则化正交匹配追踪算法(SROMP),该算法利用相关性重建光场图像序列。几个光场图像可以用不同的基本信号的线性组合一次近似。实验结果表明,采用SROMP算法可以达到文献报道的较高准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed compressive sensing of light field
The light field camera array can be regarded as distributed source. The image sequence captured by a camera array contains the inter-correlation and intra-correlation. In order to utilize the correlation, a joint sparsity model was established to combine the light field with distributed compressive sensing, and a recovery algorithm was proposed for the model -- simultaneous regularized orthogonal matching pursuit algorithm (SROMP), which uses the correlation to reconstruct the light field image sequences. Several light field images could be approximate at once using different linear combinations of elementary signals. Experimental results show that SROMP algorithm could be used to achieve high accuracy reported in the literatures.
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