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)