Description:
This
application transforms an
NDF via histogram equalisation. Histogram equalisation is an
image-processing technique in which the distribution (between limits) of data
values in the input array is adjusted so that in the output array there are
approximately equal numbers of elements in each histogram bin. To achieve this the
histogram bin size is no longer a constant. This technique is commonly known as
histogram equalisation. It is useful for displaying features across a wide dynamic
range, sometimes called a maximum-information picture. The transformed array is
output to a new NDF.
Usage:
histeq in out [numbin]
Parameters:
IN = NDF
(Read)
The NDF structure to be transformed.
NUMBIN = _INTEGER (Read)
The number of histogram bins to be used. This should be a large number, say
2000, to reduce quantisation errors. It must be in the range 100 to 10000.
[2048]
OUT = NDF (Write)
The NDF structure to contain the transformed data
array.
TITLE = LITERAL (Read)
Title for the output NDF structure. A null
value (
!) propagates the title from the input NDF to the output NDF.
[!]
Examples:
histeq halley maxinf
The data array in the NDF called halley is
remapped via histogram equalisation to form the new NDF called maxinf. histeq
halley maxinf 10000 title="Maximum information of Halley"
The data array
in the NDF called halley is remapped via histogram equalisation to form the
new NDF called maxinf. Ten thousand bins in the histogram are required rather
than the default of 2048. The title of NDF maxinf is "Maximum information of
Halley". Notes:
If there are a few outliers in the data and most of the points
concentrated about a value it may be wise to truncate the data array via THRESH,
or have a large number of histogram bins.
Related Applications
Implementation Status: