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True compression of images using wavelets

`wcompress('c',X,SAV_FILENAME,COMP_METHOD)`

wcompress(...,'ParName1',ParVal1,'ParName2',ParVal2,...)

[COMPRAT,BPP] = wcompress('c',...)

XC = wcompress('u',SAV_FILENAME)

XC = wcompress('u',SAV_FILENAME,'plot')

XC = wcompress('u',SAV_FILENAME,'step')

The `wcompress`

command
performs either compression or uncompression of grayscale or truecolor
images.

More theoretical information on true compression is in Wavelet Compression for Images of the Wavelet Toolbox™ User's Guide.

`wcompress('c',X,SAV_FILENAME,COMP_METHOD)`

compresses
the image `X`

using the compression method `COMP_METHOD`

.

The compressed image is saved in the file `SAV_FILENAME`

.
You must have write permission in the current working directory
or MATLAB^{®} will change directory to `tempdir`

and
write the `.wtc`

file in that directory. `X`

can
be either a 2-D array containing an indexed image or a 3-D array of `uint8`

containing
a truecolor image. Both the row and column size of the image must
be powers of two.

wcompress`('c',FILENAME,...)`

loads the image `X`

from
the file `FILENAME`

which is a MATLAB Supported
Format (MSF) file: MAT-file or other image files (see `imread`

).

wcompress`('c',I,...)`

converts the indexed
image `X = I{1}`

to a truecolor image `Y`

using
the colormap `map = I{2}`

and then compresses `Y`

.

Data written to `.wtc`

files uses `uint64`

precision.
In releases previous to R2016b, data was written using `uint32`

.
If your code is affected adversely by this change, use the `legacy`

option
to compress and uncompress your data using the previous behavior.

wcompress('c',X,SAV_FILENAME,COMP_METHOD,'legacy')

The valid compression methods are divided in three categories.

Progressive Coefficients Significance Methods (

**PCSM**):MATLAB Name

Compression Method Name

`'ezw'`

Embedded Zerotree Wavelet

`'spiht'`

Set Partitioning In Hierarchical Trees

`'stw'`

Spatial-orientation Tree Wavelet

`'wdr'`

Wavelet Difference Reduction

`'aswdr'`

Adaptively Scanned Wavelet Difference Reduction

`'spiht_3d'`

Set Partitioning In Hierarchical Trees 3D for truecolor images

For more details on these methods, see the references and especially Walker and also Said and Pearlman.

Coefficients Thresholding Methods (

**CTM-1**):MATLAB Name

Compression Method Name

`'lvl_mmc'`

Subband thresholding of coefficients and Huffman encoding

For more details on this method, see the Strang and Nguyen reference.

Coefficients Thresholding Methods (

**CTM-2**):MATLAB Name

Compression Method Name

`'gbl_mmc_f'`

Global thresholding of coefficients and fixed encoding

`'gbl_mmc_h'`

Global thresholding of coefficients and Huffman encoding

### Note

The Discrete Wavelet Transform uses the periodized extension mode.

All the compression methods use parameters which have default values. You can change these values using the following syntax:

`wcompress(...,'ParName1',ParVal1,'ParName2',ParVal2,...)`

Some of the parameters are related to display or to data transform functionalities. The others are linked to the compression process itself.

`'ParName'`

=`'wname'`

or`'WNAME'`

sets the wavelet name.`ParVal`

is a character vector (see`waveletfamilies`

). The default for is*bior4.4*`'ParName'`

=`'level'`

or`'LEVEL'`

sets the level of decomposition.`ParVal`

is an integer such that:`1`

≤`level`

≤`levmax`

which is the maximum possible level (see`wmaxlev`

).The default level depends on the method:

- for

**PCSM**methods`level`

is equal to`levmax`

.- for

**CTM**methods level is equal to`fix(levmax/2)`

`ParName'`

=`'it'`

or`'IT'`

sets Image type Transform.`ParVal`

must be one of the following character vectors:`'n'`

: no transformation (default), image type (truecolor or grayscale) is automatically detected.`'g'`

: grayscale transformation type.`'c'`

: color transformation type (RGB`uint8`

).`'ParName'`

=`'cc'`

or`'CC'`

sets Color Conversion parameter if`X`

is a truecolor image.`ParVal`

must be one of the following character vectors:`'rgb'`

or`'none'`

: No conversion (default).`'yuv'`

: YUV color space transform.`'klt'`

: Karhunen-Loeve transform.`'yiq'`

: YIQ color space transform.`'xyz'`

: CIEXYZ color space transform.

`'ParName'`

=`'maxloop'`

or`'MAXLOOP'`

sets the maximum number of steps for the compression algorithm.`ParVal`

must be a positive integer or`Inf`

(default is 10).

Either of the following parameters may be used:

`'ParName'`

=`'bpp'`

or`'BPP'`

sets the bit-per-pixel ratio.`ParVal`

must be such that`0`

≤`ParVal`

≤`8`

(grayscale) or`24`

(truecolor).`'ParName'`

=`'comprat'`

or`'COMPRAT'`

sets the compression ratio.`ParVal`

must be such that`0`

≤`ParVal`

≤`100`

.

Two parameters may be used. The first is related to the threshold and the second is the number of classes for quantization.

The first one may be chosen among the five following parameters:

`'ParName'`

=`'threshold'`

or`'THRESHOLD'`

sets the threshold value for compression.`ParVal`

must be a positive (or zero) real number.`'ParName'`

=`'nbcfs'`

or`'NBCFS'`

sets the number of preserved coefficients in the wavelet decomposition.`ParVal`

must be an integer such that:`0`

≤`ParVal`

≤`'ParName'`

=`'percfs'`

or`'PERCFS'`

sets the percentage of preserved coefficients in the wavelet decomposition.`ParVal`

must be a real number such that:`0`

≤`ParVal`

≤`100`

.`'ParName'`

=`'bpp'`

or`'BPP'`

sets the bit-per-pixel ratio.`ParVal`

must be such that:`0`

≤`ParVal`

≤`8`

(grayscale) or`24`

(truecolor)`'ParName'`

=`'comprat'`

or`'COMPRAT'`

sets the compression ratio.`ParVal`

must be such that:`0`

≤`ParVal`

≤`100`

.

The second parameter sets the number of classes for quantization:

`'ParName'`

=`'nbclas'`

or`'NBCLAS'`

sets the number of classes.`ParVal`

must be a real number such that:`2`

≤`ParVal`

≤`200`

.

`'ParName'`

=`'plotpar'`

or`'PLOTPAR'`

sets the plot parameter.`ParVal`

must be one of the following character vectors or numbers:`'plot'`

or`0`

: plots only the compressed image.`'step'`

or`1`

: displays each step of the encoding process (only for**PCSM**methods).

`[COMPRAT,BPP] = wcompress('c',...)`

returns
the compression ratio `COMPRAT`

and the bit_per_pixel
ratio `BPP`

.

`XC = wcompress('u',SAV_FILENAME)`

uncompresses
the file `SAV_FILENAME`

, which contains the compressed
image, and returns the image `XC`

. Depending on the
initial compressed image, `XC`

can be a 2-D array
containing either an indexed image or a 3-D array of `uint8`

containing
a truecolor image.

`XC = wcompress('u',SAV_FILENAME,'plot')`

plots
the uncompressed image.

`XC = wcompress('u',SAV_FILENAME,'step')`

shows
the step-by-step uncompression, only for **PCSM** methods.

Christophe, E., C. Mailhes, P. Duhamel (2006), “Adaptation
of zerotrees using signed binary digit representations for 3 dimensional
image coding,” EURASIP* Journal on Image and Video
Processing*, 2007, to appear in the special issue on Wavelets
in Source Coding, Communications, and Networks, Paper ID 54679.

Misiti, M., Y. Misiti, G. Oppenheim, J.-M. Poggi (2007), *Wavelets
and their applications*, ISTE DSP Series.

Said A., W.A. Pearlman (1996), “A new, fast, and efficient
image codec based on set partitioning in hierarchical trees,”
*IEEE Trans. on Circuits and Systems for Video Technology*,
Vol. 6, No. 3, pp. 243–250.

Shapiro J.M. (1993), “Embedded image coding using zerotrees
of wavelet coefficients”,P *IEEE Trans. Signal Proc.*,
Vol. 41, No. 12, pp. 3445–3462.

Strang, G.; T. Nguyen (1996), *Wavelets and Filter
Banks*, Wellesley-Cambridge Press.

Walker J.S. (1999), “Wavelet-Based Image Compression,”
University of Wisconsin, Eau Claire, Wisconsin, USA, , Sub-chapter
of CRC Press book: *Transform and Data Compression. A Primer
on Wavelets and Their Scientific Applications*.

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