What is the potential drawback of estimating the signal to noise ratio (SNR) too high?
Too high SNR setting in both MLE and ICTM methods may lead to artifact generation. These artifacts have a different character in the MLE and ICTM method, so they will be treated separately.
Artifacts in the ICTM method due to overestimation of the SNR: <br>
There are two sources of artifacts with this class of method: amplification of noise and 'ringing' artifacts, i.e. fringes around sharp edges. Ringing artifacts are greatly suppressed in the ICTM procedure. Moreover, when you switch on 'ringing reduction' the ICTM procedure will lower the SNR setting when it detects the onset of ringing. The drawback of this feature is that it increases the data dependency of the procedure. So, when you are planning to restore and compare a number of images of the same type, we do advise you not to use this switch. More troublesome is noise amplification. The amplification increases with the number of iterations. Most notably it shows up as semi-periodic structures in the background. The ICTM method can be used with the background correction option. This enables you to set the background to the average value of the background. Use Analysis->background from the Operations window to inspect the background. This feature will enable you to remove the background including the ringing phenomena effectively. Conclusion: overestimation of the SNR (say by a factor of 2) won't do much harm. However, since noise amplification artifacts may also occur inside the object, be careful with high SNR values (>100) in combination with large number of iterations (>100).
Artifacts in the MLE method due to overestimation of the SNR: <br>
Due to the build-in background correction and its optimal treatment of background (nearly always Poisson type) noise the MLE method is hardly sensitive to background noise amplification. For noisy images, amplification of noise within the object is also less than in the ICTM method. Overestimation of the SNR value in noisy images will result in reduced noise suppression. A potential danger of overestimation of the SNR parameter (>100) in low noise images is 'over-restoration', i.e. objects are estimated too small. This occurs in combination with high iteration counts, >100. With settings of the SNR parameter below 30 there is not much danger in over-restoring the object. Conclusion: for restoration of high noise images the MLE method is quite safe: there is a straightforward trade-off between noise and resolution gain.
Keywords: SNR MLE ICTM noise artifact generation ringing
Categories: Faq Deconvolution, Faq Microscopy, Huygens Faq, Imported Faqs
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