table of contents
LIPSIA     Convolution with a Gaussian filter or its derivative
vgauss
'vgauss' convolves an image with a Gaussian filter or a filter that is the partial derivative of a Gaussian. Each input image is filtered to produce a corresponding output image.

vgauss -in image.v -out filtered.v -sigma 2

Three types of filtering operations are supported:

smooth This convolves the input image with a 1D Gaussian filter in both the x and y directions

xgrad This convolves the input image with a 1D Gaussian filter in the y direction, and a 1D derivative-of-Gaussian filter in the x direction.

ygrad This convolves the input image with a 1D Gaussian filter in the x direction, and a 1D derivative-of-Gaussian filter in the y direction.

Note that the x direction is the direction of increasing column index, and the y direction is the direction of decreasing row index. When computing pixel values near an image border, the region outside of the input image is padded with border pixel values.

The input images can have pixel values of any type. In general, the output images are created with pixel values of the same type as the input images. However, if an input image has unsigned pixels (i.e., bit or ubyte) and convolution with the partial derivation of a Gaussian is required, then the input image will be converted to an image with sbyte pixels before convolution, and the output image will also have sbyte pixels.

Parameters of 'vgauss':
-help
Prints usage information.
-in
Input files. Default: (none)
-out
Output file. Default: (none)
-sigma
Standard deviation of Gaussian filter. Default: 1
-size
Filter size (pixels). Default: 0
-verbose
Show program messages. Default: 0


Max Planck Institute for Human Cognitive and Brain Sciences. Further Information: lipsia@cbs.mpg.de
Copyright © 2007 Max Planck Institute for Human Cognitive and Brain Sciences. All rights reserved.