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首页> 外文期刊>Applied optics >SIGNAL-TO-NOISE COMPARISON OF DECONVOLUTION FROM WAVE-FRONT SENSING WITH TRADITIONAL LINEAR AND SPECKLE IMAGE RECONSTRUCTION
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SIGNAL-TO-NOISE COMPARISON OF DECONVOLUTION FROM WAVE-FRONT SENSING WITH TRADITIONAL LINEAR AND SPECKLE IMAGE RECONSTRUCTION

机译：传统线性和斑点图像重建的波前传感反卷积信噪比较

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摘要

It is well known that atmospheric turbulence severely degrades the performance of ground-based imaging systems. Techniques to overcome the effects of the atmosphere have been developing at a rapid pace over the past 10 years. These techniques can be grouped into two broad categories: predetection and postdetection techniques. A recent newcomer to the postdetection scene is deconvolution from wave-front sensing (DWFS). DWFS is a postdetection image-reconstruction technique that makes use of one feature of predetection techniques. A wave-front sensor (WFS) is used to record the wave-front phase distortion in the pupil of the telescope for each short-exposure image. The additional information provided by the WFS is used to estimate the system's point-spread function (PSF). The PSF is then used in conjunction with the ensemble of short-exposure images to obtain an estimate of the object intensity distribution through deconvolution. With the addition of DWFS to the suite of possible postdetection image-reconstruction techniques, it is natural to ask ''How does DWFS compare with both traditional linear and speckle image-reconstruction techniques?'' In the results we make a direct comparison based on a frequency-domain signal-to-noise-ratio performance metric. This metric is applied to each technique's image-reconstruction estimator. We find that DWFS nearly always results in improved performance over the estimators of traditional linear image reconstruction such as Wiener filtering. On the other hand, DWFS does not always outperform speckle-imaging techniques, and in cases that it does the improvement is small. [References: 20]
机译：众所周知，大气湍流严重降低了地面成像系统的性能。在过去的十年中，克服大气影响的技术发展迅速。这些技术可以分为两大类：检测前技术和检测后技术。后检测领域的新近出现是从波前感测（DWFS）解卷积。 DWFS是一种检测后图像重建技术，它利用了检测前技术的一个功能。波前传感器（WFS）用于记录每个短曝光图像在望远镜光瞳中的波前相位失真。 WFS提供的附加信息用于估计系统的点扩展函数（PSF）。然后，将PSF与短曝光图像的整体结合使用，以通过反卷积获得物体强度分布的估计值。在将DWFS添加到可能的检测后图像重建技术套件中之后，自然会问“ DWFS与传统的线性和散斑图像重建技术相比如何？”在结果中，我们基于频域信噪比性能指标。该指标适用于每种技术的图像重建估算器。我们发现，与传统的线性图像重建（例如维纳滤波）的估计量相比，DWFS几乎总能提高性能。另一方面，DWFS并不总是比散斑成像技术好，在这种情况下，改进很小。 [参考：20]

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