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On the accuracy of PSF representation in image restoration

机译:PSF表示在图像复原中的准确性

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Point spread function (PSF) models derived from physical optics provide a more accurate representation of real blurs than simpler models based on geometrical optics. However, the physical PSF models do not always result in a significantly better restoration, due to the coarse sampling of the recording device and insufficiently high signal-to-noise ratio (SNR) levels. Low recording resolutions result in aliasing errors in the PSF and suboptimal restorations. A high-resolution representation of the PSF where aliasing errors are minimized is used to obtain improved restorations. The SNR is the parameter which ultimately limits the restoration quality and determines the need for an accurate PSF model. As a rule of thumb, the geometrical PSF can be used in place of the physical PSF without significant loss in restoration quality when the SNR is less than 30 dB.
机译:与基于几何光学的简单模型相比,源自物理光学的点扩展函数(PSF)模型可以更准确地表示真实的模糊。但是,由于记录设备的粗采样和信噪比(SNR)等级过高,物理PSF模型并不总是能够带来明显更好的恢复效果。较低的记录分辨率会导致PSF中出现锯齿错误,并且恢复效果欠佳。 PSF的高分辨率表示,其中混叠误差最小化,可用于获得改进的修复效果。 SNR是最终限制恢复质量并确定对精确PSF模型的需求的参数。根据经验,当SNR小于30 dB时,可以使用几何PSF代替物理PSF,而不会显着降低恢复质量。

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