===========================================================
        ___ _   _ ___   _     __  __   _   ___     
       / __| | | |   \ /_\   |  \/  | /_\ | _ \    
      | (__| |_| | |) / _ \  | |\/| |/ _ \|  _/    
       \___|\___/|___/_/_\_\_|_|__|_/_/_\_\_|_ ___ 
            / __| | | | _ \ __| _ \___| _ \ __/ __|
            \__ \ |_| |  _/ _||   /___|   / _|\__ \
            |___/\___/|_| |___|_|_\   |_|_\___|___/
                                               2012
     
        by Jens Wetzl           ([email protected])
       and Oliver Taubmann ([email protected])
     
       This work is licensed under a Creative Commons     
       Attribution 3.0 Unported License. (CC-BY)
       http://creativecommons.org/licenses/by/3.0/
      
===========================================================

This is a cross-platform, CUDA-based C++ implementation of 
the framework proposed in our paper "GPU Accelerated 
Time-of-Flight Super-Resolution for Image-Guided Surgery". 
It employs a maximum a posteriori (MAP) estimation to 
super-resolve an arbitrary, preregistered grayscale image 
sequence to obtain a single new image of improved quality 
and resolution. In particular, it can be used to enhance 
depth maps from range sensors such as Time-of-Flight 
cameras.

If you use this framework in your research, please cite:

Wetzl, J., Taubmann, O., Haase, S., Köhler, T., Kraus, M., 
and Hornegger, J. (2013). GPU-Accelerated Time-of-Flight 
Super-Resolution for Image-Guided Surgery. In Meinzer, 
H.-P., Deserno, T. M., Handels, H., and Tolxdorff, T., 
editors, Bildverarbeitung für die Medizin 2013, Informatik
aktuell, pages 21–26. Springer Berlin Heidelberg.

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  DEPENDENCIES
===========================================================

To use this software, you need:

- CMake (http://www.cmake.org/) for generating build files 
  of your choice.

- The Nvidia GPU Computing Toolkit and SDK
  (http://www.nvidia.com/object/cuda_home_new.html).
  
- CUDA L-BFGS (https://github.com/jwetzl/CudaLBFGS), our 
  own library for GPU-accelerated nonlinear optimization.
  
- FreeImage (http://freeimage.sourceforge.net/), a 
  lightweight image IO library. Note: This can easily be 
  replaced with your preferred tool by adapting 
  ImageIO.{h,cpp} accordingly.

===========================================================
  BUILDING
===========================================================

The default settings should be fine for regular use, but 
there are some options, you can

- enable error checking and timing

- choose not to store the transpose of the system matrix.
  This will increase computation time but decrease the 
  memory footprint.

===========================================================
  USAGE
===========================================================

The superres binary displays a usage message when you run
it without parameters.