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A compressive sensing based transmissive single-pixel camera

机译:基于压缩感测的透射式单像素相机

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Compressive sensing (CS) has recently emerged and is now a subject of increasing research and discussion, undergoing significant advances at an incredible pace. The novel theory of CS provides a fundamentally new approach to data acquisition which overcomes the common wisdom of information theory, specifically that provided by the Shannon-Nyquist sampling theorem. Perhaps surprisingly, it predicts that certain signals or images can be accurately, and sometimes even exactly, recovered from what was previously believed to be highly incomplete measurements (information). As the requirements of many applications nowadays often exceed the capabilities of traditional imaging architectures, there has been an increasing deal of interest in so-called computational imaging (CI). CI systems are hybrid imagers in which computation assumes a central role in the image formation process. Therefore, in the light of CS theory, we present a transmissive single-pixel camera that integrates a liquid crystal display (LCD) as an incoherent random coding device, yielding CS-typical compressed observations, since the beginning of the image acquisition process. This camera has been incorporated into an optical microscope and the obtained results can be exploited towards the development of compressive-sensing-based cameras for pixel-level adaptive gain imaging or fluorescence microscopy.
机译:压缩感测(CS)最近出现,并且现在正在成为越来越多的研究和讨论的主题,并且以令人难以置信的速度取得了重大进展。 CS的新颖理论从根本上为数据获取提供了一种新方法,它克服了信息论的常识,特别是Shannon-Nyquist采样定理所提供的常识。也许令人惊讶的是,它预测某些信号或图像可以从以前被认为是高度不完整的测量(信息)中准确,有时甚至是准确地恢复。由于当今许多应用程序的需求经常超过传统成像体系结构的功能,因此人们对所谓的计算成像(CI)的兴趣日益增加。 CI系统是混合成像仪,其中计算在成像过程中起着核心作用。因此,根据CS理论,我们提出了一种透射型单像素相机,该相机集成了液晶显示器(LCD)作为非相干随机编码设备,自图像采集过程开始以来,就产生了CS典型的压缩观测结果。该相机已被整合到光学显微镜中,所获得的结果可用于开发基于压缩感测的相机,用于像素级自适应增益成像或荧光显微镜。

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