Filtering
Spatial Domain Linear Filters
Applies the Canny edge-detection method to an image
Performs smoothing on 1D, 2D or 3Dimage arrays
Computes a 1D or 2D spatial Gaussian filter kernel
Performs 1D, 2D or 3D convolution on signals, images, and volumes
Creates a spatial filter object, given a kernel and other appropriate fields
Reads an ASCII text or XDR file depending on whether the file contains a spatial or spectral filter (respectively)
Saves a 2D convolution kernel to an ASCII text file
Frequency Domain Linear Filters
Generates a 2D Butterworth or ideal lowpass, bandpass, bandstop or highpass spatial frequency domain filter
Generates a 3D ideal notch spatial frequency domain filter
Computes and applies a parametric Wiener filter to an image that is either in the spatial or the spatial frequency domain
Nonlinear and Adaptive Filters
Performs 1D, 2D or 3D adaptive double-window-modified trimmed mean filter
Performs 1D, 2D or 3D adaptive minimum mean-squared error filtering
Performs nonlinear filtering operations on 1D, 2D, or 3D image arrays
Windowing
Computes one of several different data windows: Blackman, Chebyshev, Hamming, Hanning, Kaiser, rectangular, or triangular