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首页> 外文期刊>Optics Communications: A Journal Devoted to the Rapid Publication of Short Contributions in the Field of Optics and Interaction of Light with Matter >Compressed sensing imaging system based on improved theoretical model and its weighted iterative strategy
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Compressed sensing imaging system based on improved theoretical model and its weighted iterative strategy

机译:基于改进理论模型及其加权迭代策略的压缩传感影像系统

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摘要

Based on the characteristic analysis of the traditional block-based compressed sensing system, an improved compressed sensing theory model is proposed in this paper, and its hardware implementation scheme and the overall system workflow are specified according to the model requirements. Compared with the traditional block-based compressed sensing system, the linear array detector is used instead of the area array detector in the system, and the one-dimensional encoding is adopted instead of the two-dimensional encoding to simplify the encoding process. The experimental results show that the system proposed by this paper can significantly improve the image quality compared with the block-based compressed sensing system under the same system conditions, and eliminate the block effect that is common in the block-based compressed sensing system. On the basis of the proposed system, a weighted iterative restoration strategy based on frequency estimation is proposed. By adaptively adjusting the restoration process and optimizing the distribution of computing resources, the image quality is further improved.
机译:基于传统基于块的压缩传感系统的特性分析,本文提出了一种改进的压缩感探测理论模型,并根据模型要求指定其硬件实现方案和整个系统工作流程。与基于传统的基于块的压缩感测系统相比,使用线性阵列检测器代替系统中的区域阵列检测器,采用一维编码而不是二维编码来简化编码过程。实验结果表明,与在相同的系统条件下,本文提出的系统可以显着提高图像质量,并在相同的系统条件下消除基于块的压缩传感系统中常见的块效果。在提出的系统的基础上,提出了一种基于频率估计的加权迭代恢复策略。通过自适应地调整恢复过程并优化计算资源的分布,图像质量进一步提高。

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