The examples about this methods are under npgEx
folder with filenames
ended with Ex
, where the code can reproduce the figures appear in our
paper. The algorithm implementations are under folder npg
, which use the
some utility functions under utils
folder.
- R. Gu and A. Dogandžić. (Feb. 2015). Reconstruction of nonnegative sparse signals using accelerated proximal-gradient algorithms. arXiv: 1502.02613.
####2. Beam Hardening Correction Algorithms
All examples and data for our blind beam hardening correction method are
under folder bhcEx
with filenames ended with Ex
. The figures in our
paper can be reproduced by first run *Ex
, e.g., yangEx
, followed by
*Ex('plot')
, e.g., yangEx('plot')
. Algorithm implementations are under
bhc
.
-
R. Gu and A. Dogandžić, Beam hardening correction via mass attenuation discretization, in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., Vancouver, Canada, May 2013, pp. 1085–1089.
-
R. Gu and A. Dogandžić. (Sep. 2015). Polychromatic X-ray CT Image Reconstruction and Mass-Attenuation Spectrum Estimation. arXiv: 1509.02193.
To install this package, first download the repository by running
git clone https://github.com/isucsp/imgRecSrc.git
after downloading, from MATLAB change your current folder to imgRecSrc/
and first execute setupPath.m
to add necessary paths to the environment.
For X-ray CT examples, the projection and back projection operator
subroutines may be called from MATLAB. Since they are written in c
language, to prepare MATLAB recognizable MEX
files, go to imgRecSrc/prj
and compile the necessary files. Instructions on compiling the code are
provided for both UNIX
and Windows
:
require: gcc, cuda toolkit (optional) and GPU (optional)
Execute make cpu
to compile all cpu implementations. If you have GPU
equipped, run make gpu
to compile GPU implementation of the X-ray CT
projection operators. The matlab code will automatically choose to run on
GPU if equipped.
If errors are reported while compiling the *.c
/*.cu
files under
imgRecSrc/prj
, please edit the first few lines in
imgRecSrc/prj/Makefile
to make sure the path for your CUDA
installation
is correct.
require: Visual Studio, cuda toolkit (optional) and GPU (optional)
Execute imgRecSrc/setupPath.m
can automatically compile all needed files
and add paths.
If there is a GPU equipped in your PC, follow the following steps:
-
Open the
VS Native Tools Command Prompt
viaStart -> Microsoft Visual Studio -> Visual Studio Tools
; -
Use
cd
command to change directory to yourimgRecSrc/prj
; -
Run
nvcc -c gpuPrj.cu
to generate theobj
file; -
Execute
imgRecSrc/setupPath.m
.