tvreg: Variational Image Restoration and Segmentation

The tvreg package applies total variation (TV) regularization to perform image denoising, deconvolution, and inpainting. Three different noise models are supported: Gaussian (L2), Laplace (L1), and Poisson. The implementation solves the general TV restoration problem

Min TV(u) + ∫ λ F(K*u,f) dx,
u

to perform denoising, deconvolution, and inpainting as special cases. It is efficiently solved using the split Bregman method. Also included is an implementation of Chan-Vese two-phase segmentation. All functions support grayscale, color, and arbitrary multichannel images.

Please see the included documentation file tvreg.pdf for details.

=== Get Started Quickly in MATLAB ===

Compiling is not required to use tvreg in MATLAB. Try the demos

tvdenoise_demo Total variation denoising demo
tvdeconv_demo Total variation deconvolution demo
tvinpaint_demo Total variation inpainting demo
chanvese_demo Chan-Vese segmentation demo

For improved performance, run the included script "complex_mex.m" to compile the main computation routines as MEX functions. This requires that FFTW is installed, please see section 7.3 of the documentation.

=== Get Started Quickly in C/C++ ===

1. Install the FFTW library (http://www.fftw.org). Windows users can download precompiled DLL files from http://www.fftw.org/install/windows.html.

2. Compile the programs with GCC using "make -f makefile.gcc" or Microsoft Visual C++ using "nmake -f makefile.vc". See section 7 of the documentation for help.

3. Try the demos

tvdenoise_demo Total variation denoising demo
tvdeconv_demo Total variation deconvolution demo
tvinpaint_demo Total variation inpainting demo
chanvese_demo Chan-Vese segmentation demo