wavelet — perform a haar wavelet decomposition/reconstruction
wavelet [-1 ] [-2 ] [-d ] [-r ] [-#
channels] [ -t [
s ]] [-w
The wavelet command will perform Haar wavelet decomposition or reconstruction transforms on the input dataset. The command line options are:
perform a 1-dimensional (horizontal) transform.
perform a 1-dimensional (interleaved horizontal and vertical) transform.
Indicates the number of values in each sample point. For example, to perform
a transform on a
file properly, specify "-# 3". This causes the red, green and blue channels
to be transformed individually.
specifies the data type of the input, and hence the data type in which the
wavelet calculations will be performed.
The letters each stand for the first
character of the C programming language data type:
Note that if lossless decomposition
and reconstruction are desired, then data sets should be converted to the next
larger data type before being processed.
Specify the number of samples per scanline.
Specify the number of scanlines in the dataset
Specify both width and scanlines simultaneously (square image).
Specifies the width of the output image. Normally this is 1 for a full
decomposition/reconstruction. You may specify a width at which decomposition or reconstruction
should stop. This number should be a power of 2. The result will be an
"average" image of the specified size, with the remainder of the original
data width converted to "detail" coefficients. See also: -R
Resumes a transform that left off with an average image of avg_size.
This is the same as the
option. It implies the square size for a 2D decomposition limit.
decompose -# 3 < img.pix | pix-fb
will display the horizontal decomposition of the file img.pix.
decompose -# 3 -s 1024 -l 64 < img.pix >
will decompose a 1024x1024 image. The decomposition will stop when the
image has been decomposed to 64x64. The output image will thus have a 64x64
version of the original in the lower left corner of the image, with detail
terms in the remainder.
This software is Copyright (c) 1999-2016 by the United States Government as represented by U.S. Army Research Laboratory.