Using low-pass filters

Low-pass filters pass only the low-frequency information or the gradual gray-level changes. They produce images that appear smooth or blurred when compared to the original data. For non-radar image data, the following low-pass filters are available:

Average Filter

Smooths the image data to eliminate noise. A 3x3 filter kernel computes the sum of all pixels in the filter kernel and divides the sum by the total number of pixels in the kernel.

Median Filter

Also smooths your image data, but computes the median values within a rectangular filter window surrounding each pixel. This has the effect of smoothing the image and preserving edges.

In a 3x3 kernel, the median filter finds the median pixel value, the middle value in an ordered set, where an equal number of values are below and above the median. For example, 8 is the median value for the following 3x3 kernel in a gray-level values set:

Mode Filter

Computes the mode of the gray-level values that occur most frequently in the filter kernel. For example, in a 3x3 filter window with the following pixel values, the filtered pixel value of 3 occurs five times.

The mode filter is calculated as follows:

Mode filters are typically used to clean up thematic maps for presentation purposes. This filter replaces small island themes with their larger surrounding themes. With the mode filter, the maximum kernel size is 7x7. The filter window can be rectangular.

Sometimes, two values can be equally distributed within the kernel sample. In such cases, if the center value is one of the competing values, it becomes the kernel sample value. If not, the first instance of the competing values becomes the sample value.

For example, in a 3x3 filter window with the following pixel values, the pixel values 3 and 5 each occur three times. In this case the Mode pixel of the filter kernel is calculated as follows:

Neither 3 nor 5 is at the center of the kernel. The 5 in the top row is encountered first and therefore becomes the mode value.