Biomedical Engineering Reference
In-Depth Information
Fig. 6.14. Examples of line-by-line (polynomial fitting) based levelling artefacts. The left image of
nanoparticles is unlevelled. The middle image shows an artefact caused by polynomial line-by-line
levelling - the particles seem to be sitting in lowered 'trenches' in the background. The correctly
levelled image is shown on the right.
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Fig. 6.15. Example of image distortion by filtering. The image of nanoparticles on the left shows
considerable noise. Low-pass filtering (smoothing) produced the image on the right. The line profile
shows that noise was reduced, but the shapes of the two particles in the line profile were also
changed.
any, were applied to the data, because the results from filtered images can be very
misleading. For example, low-pass (or smoothing) filters tend to greatly reduce noise in
AFM images, but can also introduce artefacts such as changing the shape of features, and
increasing the apparent sharpness of steps. An example of filtering artefacts is shown in
Figure 6.15.
 
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