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Adaptive Basis Scan by Wavelet Prediction for Single-Pixel Imaging

机译:小波预测的自适应基础扫描用于单像素成像

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Single-pixel camera imaging is an emerging paradigm that allows high-quality images to be provided by a device only equipped with a single point detector. A single-pixel camera is an experimental setup able to measure the inner product of the scene under view—the image—with any user-defined pattern. Postprocessing a sequence of point measurements obtained with different patterns permits to recover spatial information, as it has been demonstrated by state-of-the-art approaches belonging to the compressed sensing framework. In this paper, a new framework for the choice of the patterns is proposed together with a simple and efficient image recovery scheme. Our goal is to overcome the computationally demanding ℓ1 -minimization of the compressed sensing. We propose to choose patterns among a wavelet basis in an adaptive fashion, which essentially relies onto the prediction of the significant wavelet coefficients’ location. More precisely, we adopt a multiresolution strategy that exploits the set of measurements acquired at coarse scales to predict the set of measurements to be performed at a finer scale. Prediction is based on a fast cubic interpolation in the image domain. A general formalism is given so that any kind of wavelets can be used, which enables one to adjust the wavelet to the type of images related to the desired application. Both simulated and experimental results demonstrate the ability of our technique to reconstruct biomedical images with improved quality compared with compressive-sensing-based recovery. Application to the real-time fluorescence imaging of biological tissues could benefit from the proposed method.
机译:单像素相机成像是一种新兴的范例,它允许仅配备有单点检测器的设备提供高质量的图像。单像素相机是一种实验性设置,可以使用任何用户定义的图案来测量被查看场景的内部产品(图像)。对经过不同模式获得的一系列点测量值进行后处理,可以恢复空间信息,正如属于压缩传感框架的最新方法所证明的那样。本文提出了一种模式选择的新框架,并提出了一种简单有效的图像恢复方案。我们的目标是克服压缩感测在计算上的ℓ1-最小化。我们建议以自适应方式在小波基础上选择模式,这主要取决于对重要小波系数位置的预测。更准确地说,我们采用了一种多分辨率策略,该策略利用在粗略尺度上获得的一组测量结果来预测将在更精细尺度上进行的一组测量。预测基于图像域中的快速三次插值。给出了一种一般形式,以便可以使用任何种类的小波,这使得人们可以将小波调整为与所需应用程序相关的图像类型。模拟和实验结果均表明,与基于压缩感测的恢复相比,我们的技术能够以更高的质量重建生物医学图像。该方法可应用于生物组织的实时荧光成像。

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