68 PART IV Digital Documentation
offer a higher signal quality than small pixels. So for best resolution, you need
enough light to get a decent signal from your pixels, or else your camera needs
a sufficiently low noise level to work well at lower light levels. That’s the point:
finding
the right compromise is always key in microscopy.
To match Abbe’s formula with Nyquist’s theorem for a given objective, you can
use a camera adapter.
If you have microscope camera with a pixel size of 6.45 m, a
20× objective and a 1.0 camera adapter, the resulting pixel size
in your sample area is:
6.45 m: 20 1.0 0.32 m size of pixel in sample area
Now, using the Nyquist criterion:
6,45 μm x 2.3 / (20 x 1.0) = 0,74 μm size of resolvable structures in
sample. This number must match the optical resolution of the lens.
Binning is the process of combining a cluster of pixels into a single
pixel.
Binning
Camera sensitivity can be increased by combining photo-generated signal charges
from neighboring pixels. With CCD cameras, this can be done during readout of
the charge so this also increases the camera frame rate. Sensitivity is increased, as
the readout noise is added only once per binned pixel information and the signal
amplitude is enlarged according to the squared binning number, as compared to
multiple single readouts.
With CMOS cameras, this can be done only after readout by digitally adding the
values of neighboring pixels so that no speed improvement can be reached. Sensitivity
is increased since the readout noise is reduced by the binning number and
the signal amplitude is increased.
One severe side effect is the loss of image resolution as the effective pixel area is
enlarged. Binning factors can range from 1 × 1 (no binning) up to multiple pixels
such as 5 × 5. Binning reduces the amount of image data produced as the resulting
pixel count is decreased. As the sensitivity is increased, you can increase the
acquisition speed due to possible shorter exposure times.