Signal to Noise ratio

In the Huygens Software the Signal-to-Noise ratio (SNR) is treated as a regularization parameter, i.e., a means to control the sharpness of the deconvolution result.

Yet, one should be aware of the effect of extreme SNR values on image deconvolution: too high SNR values can produce restoration artifacts; too low SNR values can lead to smooth structures.

Note

After a little practice it is possible to assess the SNR range for deconvolution visually. Notice that the SNR should increase with the quality of the raw data.

There are different acquisition settings that have an impact on the quality of the recorded signal. Changing these in the experimental setup will most likely require a modification of the SNR value for deconvolution. These acquisition settings are:

• Gain / offset
• Time exposure / scanning velocity
• Summing / averaging
• Laser power
• Spectral detection range

Because these settings are typically different for each channel HRM will require an SNR value per channel, like this:

As a guide, here the typical values for different microscopy tecniques:

• Confocal: between 20 and 40.
• STED: between 10 and 20.
• Widefield: between 40 and 60.

HRM offers an estimator to further help you find good SNR values for the deconvolution runs. Click on to use the SNR estimator.

In a new page you will be asked to select an SNR estimation method.

The beta method gets good estimations on images without a baseline. When working with images that contain a baseline the classic method can be used instead.

Next, select an image that represents the acquisition run of the batch that is to be deconvolved in this job. Press for the SNR estimation:

The output of the SNR estimator shows (per channel) a thumbnail next to 4 different noise simulations of the same region. In bold letters the SNR of the simulation that most resembles the original image.

By pressing the estimated SNR values are copied into the restoration parameter template.