NAME

       wzip - lossy data compression and denoising

SYNOPSIS

       wzip [ -c | -d | -dn | -hdn ] num sf

DESCRIPTION

       This manual page documents the wzip command.

       wzip  is  a  program  that can be used for LOSSY data compression and denoising.  It reads
       from STDIN and writes to STDOUT. In compression mode the input  is  a  sequence  of  ascii
       floating-point  values.   num is the number of these data values. The output is a sequence
       of small integers, most of them zero in typical application. This is ready  for  effective
       compression with a standard loss-less compression program like gzip.

       The  program  can  also  be  used  for  denoising.  In this case both input and output are
       sequences of ascii floating-point values.

       The scale factor sf determines the strength of compression or denoising.  A  higher  scale
       factor  means  heavier  compression  and  stronger  denoising.   Four  times  the standard
       deviation of the noise content is a good start.  Otherwise 5 percent of the overall signal
       amplitude might be used as a first estimation of a suitable scale factor.

       If  the noise content of the input data is strongly non-Gaussian-distributed, like Poisson
       noise. The input data should be transformed to approximate Gaussian-distributed noise.  If
       the input values are Poisson-distributed, that means for example raw counts per channel in
       EDX or  XPD,  they  can  be  transformed  to  approximate  Gaussian-distributed  noise  by
       transformation of each data point with y:=2.0*sqrt(x+0.25109). Back transformation is done
       with y:=(x/2)^2. The summand 0.25109 compensates for the bias caused by the  asymmetry  of
       the Poisson-distribution.

       Invoking  the  program  without  any  options writes examples of the use of the program to
       STDERR.

OPTIONS

       There must be given exactly one option.

       -c     Compression, reads num ascii floating-point values from STDIN and writes a sequence
              of integers with high redundancy to STDOUT.

       -d     Decompression,  reads  from STDIN and writes a sequence of num ascii floating-point
              values to STDOUT. These are more or less similar to the original data.

       -dn    Denoising, reads num ascii floating-point values from STDIN and writes  a  sequence
              of num ascii floating-point values to STDOUT. These are more or less similar to the
              original data.

       -hdn   Denoising with hard thresholding instead of  wavelet  shrinkage.  Single  untouched
              noise  peaks  may  be visible with this mode. On the other hand, there is much less
              impact on the signal slope.

SEE ALSO

       Donoho, D.L.; Johnstone, I.M.: Adapting  to  unknown  smoothness  via  wavelet  shrinkage,
       technical  report 425, Department of Statistics, Stanford University, Stanford, June 1993,
       ftp://playfair.stanford.edu/pub/donoho/ausws.ps.Z

       Franzen, A.: Compression of process data with a wavelet method, steel res. 69 (1998),  No.
       1, pp. 28/30

       Franzen,  A.:  Non-linear  denoising with wavelet transformation, Z. Metallkd.  89 (1998),
       No. 4, pp. 297/302

AUTHOR

       This manual page was  written  by  Andreas  Franzen  <anfra@debian.org>,  for  the  Debian
       GNU/Linux system (but may be used by others).

       Copyright  (C)  1997 Andreas Franzen, placed under the GNU General Public License, see the
       file copyright for details.

                                         24 December 1997                                 WZIP(1)