qccwavdcttceencode.3

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

.TH QCCDCTTCEENCODE 3 "QCCPACK" ""
.SH NAME
QccWAVdcttceEncode, QccWAVdcttceDecode \-
encode/decode an image using the DCT-TCE algorithm
.SH SYNOPSIS
.B #include "libQccPack.h"
.sp
.BI "int QccWAVdcttceEncode(const QccIMGImageComponent *" image ", int " num_levels ", int " target_bit_cnt ", double " stepsize ", int " overlap_sample ", double " smooth_factor ", QccBitBuffer *" output_buffer );
.br
.BI "int QccWAVdcttceDecodeHeader(QccBitBuffer *" input_buffer ", int *" num_levels ", int *" num_rows ", int *" num_cols ", double *" image_mean ", double *" stepsize ", int *" max_coefficient_bits ", int *" overlap_sample ", double *" smooth_factor );
.br
.BI "int QccWAVdcttceDecode(QccBitBuffer *" input_buffer ", QccIMGImageComponent *" image ", int " num_levels ", double " image_mean ", double " stepsize ", int " max_coefficient_bits ", int " target_bit_cnt ", int " overlap_sample ", double " smooth_factor );
.SH DESCRIPTION
.SS Encoding
.LP
.B QccWAVdcttceEncode()
encodes an image component,
.IR image ,
using the DCT-TCE algorithm by Shah
.IR "et al" .
The DCT-TCE algorithm combines a block-based lapped biorthogonal 
transform (LBT) based on the DCT with the embedded TCE coder.
See "ALGORITHM" below for more detail.
.LP
.I image
is the image component to be coded and
.I output_buffer
is the output bitstream.
.I output_buffer
must be of
.B QCCBITBUFFER_OUTPUT
type and opened via a prior call to
.BR QccBitBufferStart (3).
.LP
The LBT is controlled by the parameters
.IR num_levels ", " overlap_sample ", and " smooth_factor .
.IR overlap_sample
and
.IR smooth_factor
are parameters to the LBT's prefilter that is applied
before its block-based DCT. Specifically,
.IR overlap_sample
is the number of samples of overlap between DCT blocks;
.IR smooth_factor
is the smoothing constant for the prefilter.
.I num_levels
specifies the block size of the block-based DCT that underlies the
LBT.
Specifically, the block size is
.RI "2^" num_levels " x 2^" num_levels .
After the LBT coefficients are reorganized into the dyadic structure,
the dyadic decomposition has 
.IR num_levels
resolution levels.
See "ALGORITHM" below for more detail.
.LP
Two encoding modes are supported.
Mode 1 consists of first applying a scalar quantizer to all
transform coefficients and then encoding the coefficients,
bitplane by bitplane, until all bitplanes are encoded.
Mode 2 consists of direct bitplane encoding without any
scalar quantization of coefficients; in this mode, encoding
stops when the target bitrate is reached.
Mode 1 is selected by specifying a quantization
.I stepsize
that is greater than zero.
If
.I stepsize
is less than or equal to zero, then
Mode 2 is selected. In this case, a target encoding bit count,
.I target_bit_cnt
must be specified.
.LP
Since the input image is partitioned into blocks for the DCT that
underlies the LBT,
.IR image
must have size that is an integer multiple of the DCT block size in
both directions.
.BR QccWAVdcttceEncode()
returns in error if this is not the case.
.SS Decoding
.LP
.B QccWAVdcttceDecodeHeader()
decodes the header information in the bitstream in the input
.I input_buffer
(which must be of
.B QCCBITBUFFER_INPUT
type and opened via a prior call to
.BR QccBitBufferStart (3)).
The header information is returned in
.I num_levels
(number of levels of wavelet decomposition),
.I num_rows
(vertical size of image),
.I num_cols
(horizontal size of image),
.I image_mean
(the mean value of the original image),
.I stepsize
(quantization stepsize),
.I max_coefficient_bits
(the number of bits used to represent the magnitude of the coefficient with largest absolute value),
.I overlap_sample
(the number of samples of overlap between DCT blocks), and
.I smooth_factor
(the smoothing factor to the pre/postfiler).
.LP
.B QccWAVdcttceDecode()
decodes the bitstream
.IR input_buffer ,
producing the reconstructed image component,
.IR image .
The bitstream must already have had its header read by a prior call
to
.B QccWAVdcttceDecodeHeader()
(i.e., you call
.B QccWAVdcttceDecodeHeader() 
first and then
.BR QccWAVdcttceDecode() ).
.SH "ALGORITHM"
The DCT-TCE algorithm couples
the TCE image coder (Tian and Hemami, 2004)
with the lapped biorthogonal transform (LBT) due to Tran
.IR "et al" .
The forward LBT is implemented using
a block-based discrete cosine transform (DCT) equipped
with prefiltering that overlaps the DCT blocks.
The prefilter reduces intra-block and
inter-block correlation of the block-based coefficients, resulting in
coefficients that are less correlated and thereby more suitable to
the tarp filtering that underlies TCE.
For the DCT-TCE algorithm, the forward and inverse
LBT are accomplished via calls to
.BR QccIMGImageComponentLBT (3)
and
.BR QccIMGImageComponentInverseLBT (3),
respectively.
.LP
During encoding, after the LBT is performed,
the LBT coefficients are rearranged into a
pyramid structure similar to that of a dyadic DWT pyramid;
this dyadic pyramid has
.IR num_levels
resolution levels, where the block size of the DCT blocks is
.RI "2^" num_levels " x 2^" num_levels .
At this point, the TCE image coder is applied to the
resulting "subbands" in a manner identical to that of the
original wavelet-based TCE coder.
In decoding, after the TCE decoder assmebles the dyadic pyramid from
the bitstream, the reconstructed LBT coefficients are rearranged into
their original block-based organization before the inverse LBT is
performed.
.SH "SEE ALSO"
.BR dcttceencode (1),
.BR dcttcedecode (1),
.BR QccIMGImageComponentLBT (3),
.BR QccIMGImageComponentInverseLBT (3),
.BR QccPackWAV (3),
.BR QccPackIMG (3),
.BR QccPack (3)

.LP
V. P. Shah, J. E. Fowler, and N. H. Younan, "Tarp Filtering of
Block-Transform Coefficients for Embedded Image Coding," in
.IR "Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing" ,
Toulouse, France, May 2006, vol. 2, pp. 21-24.

C. Tian and S. S. Hemami, "An Embedded Image Coding System
Based on Tarp Filter with Classification," in
.IR "Proceedings of the International Conference on Acoustics, Speech, and Signal Processing" ,
Montreal, Quebec, Canada, May 2004, vol. 3, pp. 49-52.

T. D. Tran, J. Liang, and C. Tu, "Lapped transform via time-domain
pre- and post-filtering,"
.IR "IEEE Transactions on Signal Processing" ,
vol. 51, no. 6, pp. 1557-1571, June 2003.

C. Tu and T. D. Tran, "Context-based entropy coding of
block transform coefficients for image compression,"
.IR "IEEE Transactions on Image Processing" ,
vol. 11, no. 11, pp. 1271-1283, November 2002.

.SH AUTHOR
Written by Vijay Shah, Mississippi State University

Copyright (C) 1997-2009  James E. Fowler
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