Basic Description: Linear is a linear filter operation that can be used to run lowpass filters (average, disk, or Gaussian) to smooth the data, and high pass filters (Laplacian, log, and unsharp) to accent edges and transitions.
Technical Details: A linear filter is an operation where each pixel is transformed by a linear combination of pixels in the surrounding neighborhood. The neighborhood is specified by the user. The linear filter is implemented as a convolution on the tile.
Instructions: After choosing a selection method and making your selection on the survey, select a filter type from the dropdown list and follow the instruction for that filter.
average
When the average filter is selected, simply choose a kernel size and units (samples or meters) using the dropdown menus.

disk
The disk option averages values within a circular region with the specified radius (in pixels).

gaussian
The gaussian filter is a weighted average of the pixels in the defined neighborhood (i.e. the filter size). The weights of the neighboring pixels decrease with distance from the center and are based on a Gaussian curve with the specified Sigma value. Small values of sigma create a faster drop in weight with increasing distance. Typically the filter size should be chosen as 2*Sigma + 1. For example, if Sigma = 2, the filter size should be 5x5 samples. If Sigma < 1, chose the Filter Size as 3x3.

laplacian
The laplacian filter is an edge sharpening filter and is sometimes called a tophat filter because of its shape. Alpha controls the amount of sharpening with values close to one resulting in extreme, and often undesired, sharpening.

log
The LoG, or Laplacian of Gaussian filter, is another edge sharpening filter. It is identical to the Laplacian filter but the additional capacity for smoothing the tile first with a Gaussian lowpass filter. This is useful for emphasizing edges at different scales.

unsharp
Unsharp is a sharping filter commonly used in image processing. Large alpha values result in more sharpening.
