#+TITLE: NOTE ABOUT THE EXAMPLE IMAGES EMBEDDED TO THIS SOFTWARE

In order to respect image copyrights, we do not provide real SAR images in
this software. However, a *synthetic* pseudo-raw SAR image is provided in the
'data' directory in two different formats, yielding the two files:

+ '/data/u0.tif': a multipage TIFF image (first page = real part, second page
= imaginary part)

+ '/data/u0.mat': same image saved as a MAT-file (MATLAB formatted binary
file).

The image has been synthesized from a stack of 26 registered looks of
complex-valued TerraSAR-X images (*those original TerraSAR-X images are not
provided in this software*) according to the following procedure:

1. We resampled all images of the stack to the Shannon-Nyquist critical sampling
   rate (or equivalently, we removed the zero-padding from the Fourier spectrum)
   and we inverted the Hamming apodization from each image to retrieve the
   corresponding pseudo-raw.

2. We applied our speckle plus target decomposition algorithm to each image of
   the stack. Thus, each pseudo-raw image (u0) of the stack was decomposed into
   a speckle component (w0) and a target component (s0: linear combination of
   cardinal sine functions), such as u0 = w0 + s0;

3. We computed a 26-look averaging of all the 26 speckle components and this
   (real-valued) averaged image was denoised using the MuLog+BM3D algorithm
   recently proposed in

   Ch.-A. Deledalle, L. Denis, S. Tabti and F. Tupin, ``MuLoG, or How to apply
   Gaussian denoisers to multi-channel SAR speckle reduction?'', IEEE
   Transactions on Image Processing, 2017,

   yielding a reflectivity map denoted 'R'.

4. We simulated a single look observation of the reflectivity map 'R' by
   mutliplying its gray levels by a complex-valued synthetic speckle, and we
   added to this noisy image the target component 's0' extracted from the first
   image of the pseudo-raw stack.

5. The resulting image was saved as 'u0' in TIFF and MAT-File formats.

This way, we computed a realistic (but still synthetic) pseudo-raw SAR image
that we use below to illustrate the capabilities of the two algorithms provided
in this software.
