qcchyprklt.3

spiht for linux this is used to decod and encode vedio i wich all enjoy

.TH QCCHYPRKLT 3 "QCCPACK" ""
.SH NAME
QccHYPrklt \- 
data structure
.B QccHYPrklt
spectral reversible KLT transform
.SH SYNOPSIS
.B #include "libQccPack.h"
.sp
.BI "int QccHYPrkltInitialize(QccHYPrklt *" rklt );
.br
.BI "int QccHYPrkltAlloc(QccHYPrklt *" rklt );
.br
.BI "void QccHYPrkltFree(QccHYPrklt *" rklt );
.SH DESCRIPTION
QccPack provides data structure
.B QccHYPrklt
for representing a reversible KLT transform.
.LP
The components of a
.B QccHYPrklt
structure are a vector representing the dataset mean and
a matrix representing the transform itself, as determined
by a singular value decomposition of the dataset's covariance
matrix.
.SH "DATA STRUCTURE"
The
.B QccHYPrklt
data structure is defined as:
.RS
.nf

typedef struct
{
  int num_bands;
  QccVectorInt mean;
  QccMatrix matrix;
  QccMatrix P;
  QccMatrix L;
  QccMatrix U;
  QccMatrix S;
  int factored;
} QccHYPrklt;
.fi
.RE
.LP
The fields of
.B QccHYPrklt
are as follows:
.TP
.IR num_bands
The number of spectral bands the reversible KLT is designed for.
.TP
.IR mean
The mean vector (length =
.IR num_bands ).
.TP
.IR matrix
The transform matrix (size = 
.IR num_bands " x " num_bands ).
This is the original KLT matrix as trained on the data
.TP
.IR P ", " L ", " U ", " S
These matrices are the KLT matrix factored into
reversible lifting steps.
.TP
.IR factored
Indicates whether
.I matrix
has be factored into
.IR P ", " L ", " U ", " S
.SH "ROUTINES"
.B QccHYPrkltInitialize()
should be called before any use of a
.B QccHYPrklt
structure.
.B QccHYPrkltInitialize()
initializes the fields of
.I rklt
to the following values:
.RS

.IR num_bands :
0
.br
.IR mean :
.B NULL
.br
.IR matrix :
.B NULL
.br
.IR P :
.B NULL
.br
.IR L :
.B NULL
.br
.IR U :
.B NULL
.br
.IR S :
.B NULL
.br
.RE
.LP
.B QccHYPrkltAlloc()
allocates the
.IR mean ,
.IR matrix ,
.IR P ,
.IR L ,
.IR U ,
and
.IR S
fields of the reversible KLT.
.IR num_bands
must be set prior to calling
.BR QccHYPrkltAlloc() .
.LP
.B QccHYPrkltFree()
frees the 
.IR mean ,
.IR matrix ,
.IR P ,
.IR L ,
.IR U ,
and
.IR S
fields of
.IR rklt .
.SH "THEORY"
The Karhunen-Lo鑦e transform (KLT) is a data-dependent linear
transform that is optimal in the sense that it
packs the most signal energy into a given number of
transform coefficients.
The usual KLT is an irreversible transform.
A reversible KLT, on the other hand,
maps integers to integers. Such a reversible integer
KLT was proposed Hao and Shi (2003) based on reversible matrix
factorizations originating with Hao and Shi (2001).
.LP
In Hao and Shi (2001), a square transform matrix
.IR A
with determinant equal to +1 or -1 is factored as
.IR A " = " P * L * U * S
where
.IR L
and
.IR S
are lower triangular,
.IR U
is upper triangular,
and
.IR P
is a reversible permutation matrix. Implementing the
.IR U
transform using upper-triangular lifting steps and the
.IR L
and
.IR S
transforms using
corresponding lower-triangular counterparts results in a
reversible calculation of
.IR A .
Since the KLT is an orthonormal
transform (i.e., its determinant is 1), this factorization was used
in Hao and Shi (2003) to obtain a reversible
integer transform that approximates
the KLT. Here, we employ the variant using quasi-complete
pivoting proposed by Galli and Salzo.
.SH "RETURN VALUE"
These routines return 0 on success, and 1 on failure.
.SH "SEE ALSO"
.BR QccHYPrkltTrain (3),
.BR QccHYPrkltTransform (3),
.BR QccHYPrkltInverseTransform (3),
.BR QccIMGImageCube (3),
.BR QccPackHYP (3),
.BR QccPackIMG (3),
.BR QccPack (3)

P. Hao and Q. Shi, "Matrix factorization for reversible integer mapping,"
.IR "IEEE Transactions on Signal Processing" ,
vol. 49, no. 10, pp. 2314-2324, October 2001.

P. Hao and Q. Shi,
"Reversible integer KLT for progressive-to-lossless compression
of multiple component images," in
.IR "Proceedings of the International Conference on Image Processing" ,
vol. 1, Barcelona, Spain, September 2003, pp. 633-636.

L. Galli and S. Salzo, "Lossless hyperspectral compression using KLT,"
in
.IR "Proceedings of the International Geoscience and Remote Sensing Symposium" ,
vol. 1, Anchorage, AK, September 2004, pp. 313-316.

.SH AUTHOR
Copyright (C) 1997-2009  James E. Fowler
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