In the first code example, an eye chart image is convolved with a small PSF representing the optical response of a human cornea. The result represents the quality of the retinal image. The next two code examples illustrate this property and have identical results. The amount of blurring in a particular direction is proportional to extent of the region in that dimension. The code example blurs the volume image significantly in x, less so in y, and does not blur at all in the z direction.
Extents defines the effective neighborhood, as in the previous examples.
A priori knowledge of different tissue types represented by different ranges of image pixel values can be used to remove spot noise and homogenize image regions of uniform underlying tissue type. Larger neighborhoods tend to increase the amount of smoothing, but will not show appreciable effects on so small an image. The rank function simply orders the pixels in the neighborhood from smallest to largest and then uses the pixel at a preselected rank as the output. The most common type of rank filter returns the median value from the neighborhood.