Image Processing
Image processing is required before viewing or analyzing almost all AFM images. Most AFM products are supplied with very powerful image display and analysis software. Properly used, the image processing software will typically not introduce artifacts into an image. This section presents some of the common artifacts that can be introduced into AFM images by the image processing software. Leveling
As mentioned in section 2.4, most images have some tilt and bow that is introduced to the images by the scanner or stage configuration. There are a number of background subtraction options that are possible. The two most common types are: Line by line leveling - 0 to 4(th) order
Plane Leveling - 0 to 4(th) order Also, software typically allows you to exclude areas from the leveling. When an area is excluded, it is not used for the calculation of the background in the image. Low Pass Filter
A low pass filter is often used to “smooth” data before it displays. Such filters can cause steps in images to appear distorted.  Figure 22A-B: (A) High pass filtering of the step on the left results in the shape shown in (B). The amount of distortion depends on the amount of filtering applied to the image. When images are viewed that have substantial low pass filtering, the dimensions in the image can appear distorted. Other artifacts can appear as a sharpness at the edge of steps in an image. Matrix Filter/Smoothing
Matrix filtering is very effective at “smoothing” images and removing noise from the image. However, the filtering process often reduces the resolution of the image. As a rule of thumb, if the image has no noise in it, then the data has probably been compromised. Fourier Filtering   Figure 23A-B: (A) AFM image of nanospheres with no filtering. The image shows noise in the associated line profile. (B) The image generated after matrix smoothing. The line profile shows no noticeable noise and the shape of the particle is altered. Periodic structures can easily be introduced into images with Fourier filtering. This can be used for creating “atomic structure” in images. As an example, images of “white noise” can be filtered to give periodic structure that looks like atomic structure. Image Looks Too Good
If an AFM image looks too good to be true it probably is. All measurement techniques have some noise associated with them. Because AFM data is completely electronic, it is possible to take an image and alter it with image enhancement techniques to create a beautiful picture that does not represent the structure of the surface.  Figure 24: This 850 × 850 nm2 image of a nanotube had substantial noise when originally measured. Filtering added the “nodules” to the image making it seem like a much higher resolution image.
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