Help for POLYNOIS
This program produces discrete level noise (0-255). The user
must specify the noise intensity level and the noise probability.
Original Programmer : T. C. RINDFLEISCH
Current Cognizant Programmer : F. MOSS
Made Portable for UNIX: CRI 05-SEP-94
Operation:
The program must be supplied with at least one pair of
"NOISE" parameters. (i.e. noise=(10,1)) Each pair of integer
parameters consists of a noise intensity level,as the first
constant, and an associated noise probability, as the second
constant. The initial seeds for a uniform random number
generator can be optionally specified. If no value for the
random number generator is provided, then the default value
of (0,0) is used.
The probability for a noise intensity level is determined
as a ratio of the input value and the total cumulative noise
probability. For example, if three noise levels with noise
probabilities of NOP1,NOP2,and NOP3, respectively, are required,
then the actual noise probabilities are NOP1/ACC, NOP2/ACC,
and NOP3/ACC, where ACC is (NOP1+NOP2+NOP3). After the interval
between 0 and 1 is divided into subintervals proportional to the
internal probabilities (in the order specified), the value returned
by the random number generator, RAND, is checked. The associated noise
intensity level for the subinterval in which RAND falls is generated
for the current output pixel.
The noise intensity level is restricted to values equal to or
between 0 and 255, while the noise probability must be greater
than zero. A maximum of 256 pairs of integers can be specified
whether or not the default value for the random number generator
is used. The order of the pairs of integers is not important.
The maximum line length is 3600 bytes. Since there is no input
the size field determines the number of lines and samples in
the output picture.
PARAMETERS:
OUT
output data set
NLO
number of lines in the
output picture
NSO
number of samples in
the output picture
SEEDS
initial seeds for random
number generator
NOISE
noise intensity and noise,this is a required parameter
probability
See Examples:
Cognizant Programmer: