LEEFILT Function

Standard Library function that performs image smoothing by applying the Lee Filter algorithm.

Usage

result = LEEFILT(image[, n, sigma])

Input Parameters

image—A 1D, 2D, or 3D array containing a signal; signal-interleaved signals; an image; image-interleaved images; or a volume.

n—(optional) The value of 2n + 1 is used for the side of the filter box. The side of the filter box must be smaller than the smallest dimension of image. (Default: 5)

sigma—(optional) The estimate of the standard deviation. The value must be a positive. (Default: 5)

Note: If sigma is negative, you will be prompted for a value to be typed in, the value will be displayed, and the filtered image will be displayed with the TVSCL command. This cycle will continue until a zero value of sigma is entered.

Returned Value

result—A two-dimensional array containing the smoothed image.

Keywords

Edge—A scalar string indicating how edge effects are handled. (Default: 'copy') Valid strings are:

'zero'—Sets the border of the output image to zero.
'copy'—Copies the border of the input image to the output image. (Default)

Intleave—A scalar string indicating the type of interleaving of 2D input signals containing signal-interleaved signals; and 3D input arrays containing image-interleaved images, or a volume. Valid strings and the corresponding interleaving methods are:

'signal'—The 2D input image array arrangement is (x, p) for p signal-interleaved signals of length x.
'image'—The 3D image array arrangement is (x, y, p) for p image-interleaved images of x-by-y.
'volume'—The input image array is treated as a single entity.

Discussion

LEEFILT performs image smoothing by applying the Lee Filter algorithm. This algorithm assumes that the sample mean and variance of a value is equal to the local mean and variance of all values within a fixed range surrounding it. LEEFILT smooths additive signal noise by generating statistics in a local neighborhood and comparing them to the expected values.

Since LEEFILT is not computationally expensive, it can be used for near real-time image processing. It can be used on signals as well as images.