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)