# FlexBox - A **Flex**ible Primal-Dual Tool**Box**
## Introduction
**FlexBox** is a flexible MATLAB toolbox for finite dimensional convex variational problems in image processing and beyond
Nowadays, many problems in image processing consist of minimizing convex energies. Typically these problems can be written as
![Problem formulation][generalPrimalFormulation] ,
where ![A](https://latex.codecogs.com/svg.latex?A) denotes a linear operator and
![F](https://latex.codecogs.com/svg.latex?F) is a proper, convex and lower-semicontinuous function. This Problem refers to the so-called _primal_ formulation of the minimization problem and ![x in R^N](https://latex.codecogs.com/svg.latex?x\in\mathbb{R}^N) is known as the primal variable we are interested in recovering.
[generalPrimalFormulation]: https://latex.codecogs.com/svg.latex?\min_{x}&space;F(Ax) "Problem formulation"
[matA]: https://latex.codecogs.com/svg.latex?A "A"
[funcF]: https://latex.codecogs.com/svg.latex?F" "F"
## Authors
* Hendrik Dirks ([hendrik.dirks@wwu.de](mailto:hendrik.dirks@wwu.de))*
* Lars Haalck ([lars.haalck@wwu.de](mailto:lars.haalck@wwu.de))*
\*Institute for Computational and Applied Mathematics
University of Muenster, Germany
## License
**FlexBox** is copyright ©2016-2017 by Hendrik Dirks.
If you plan to distribute the software (commercially or not), please contact Hendrik Dirks for more information.
## Dependencies
In order to use the MATLAB version of FlexBox the following requirements should be met:
* Matlab >= R2015b
* Image Processing Toolbox
In order to use the C++/CUDA version please refer to the repository: https://github.com/HendrikMuenster/flexBox_CPP
## Usage
We recommend to look at the provided examples in the folder examples/.
## C++/CUDA Module
**FlexBox** comes with a C++ module which can be used stand-alone or together with MATLAB via MEX-interfaces. The C++ module can be found at https://github.com/HendrikMuenster/flexBox_CPP and it is included in this repository as a submodule in the directory flexBox_CPP. For installation instructions please read the README in the linked repository.
## Citation
If you use this toolbox please use the following citation
```
@Article{dirks2015flexbox,
Title = {A Flexible Primal-Dual Toolbox},
Author = {Dirks, Hendrik},
Journal = {ArXiv e-prints},
Year = {2016},
Month = mar,
Keywords = {Mathematics - Optimization and Control, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Mathematical Software, I.4, G.1.6, G.4},
Primaryclass = {math.OC}
}
```
A preprint of the article can be found at http://arxiv.org/abs/1603.05835
## Reporting Bugs
In case you experience any problems, please create an issue at https://github.com/HendrikMuenster/flexBox/issues or
https://github.com/HendrikMuenster/flexBox_CPP/issues
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用于图像处理及其他领域的有限维凸变分问题的MATLAB (159个子文件)
.gitignore 337B
.gitmodules 100B
hendrik.jpg 188KB
flexBox.m 13KB
basicOpticalFlow.m 11KB
warpingOperator.m 6KB
basicTerm.m 5KB
concatOperator.m 5KB
labelingTerm.m 4KB
gradientOperator.m 4KB
flowToColorV2.m 3KB
vararginParser.m 3KB
computeColor.m 3KB
blurOperator.m 3KB
generateRadonMatrix.m 3KB
convolutionOperator.m 2KB
exampleRadon.m 2KB
generateCentralGradientND.m 2KB
generateForwardGradND.m 2KB
generateBackwardGradND.m 2KB
functionHandleOperator.m 2KB
basicDualizedOperator.m 2KB
permutationOperator.m 2KB
subsamplingOperator.m 2KB
superpixelOperator.m 2KB
identityOperator.m 2KB
labelingProxDual.m 2KB
generateBlurrND.m 2KB
exampleCustomRegularizer.m 2KB
exampleOpticalFlow.m 1KB
exampleTGV.m 1KB
exampleSegmentationColor.m 1KB
basicCurl.m 1KB
basicGradientDifference.m 1KB
diagonalOperator.m 1KB
L2InfProxDual.m 1KB
exampleOperatorConcatenation.m 1KB
exampleNuclearNorm.m 1KB
basicOperator.m 1KB
exampleROF_Deblurr.m 1KB
zeroOperator.m 1KB
basicSecondOrderGradient.m 1KB
exampleFunctionHandleOperator.m 1KB
basicShear.m 1KB
exampleConstraint.m 1KB
exampleSegmentation.m 1KB
basicDivAnticurl.m 1KB
basicDivCurl.m 1KB
basicGradient.m 1KB
exampleROF.m 1KB
exampleL2Inf.m 973B
exampleInterpolationTV.m 950B
HuberProxDual.m 945B
basicHessian.m 935B
basicDivergence.m 924B
basicLaplace.m 913B
LInfDataProxDual.m 913B
KLDataProxDual.m 900B
LInfProxDual.m 857B
L1plusInnerProductGradientDifference.m 854B
nuclearProxDual.m 848B
L1plusInnerProductGradient.m 809B
innerProductGradientDiff.m 763B
L1IsoProxDualShift.m 743B
basicDualizedDataterm.m 738B
KLdataTermOperator.m 730B
innerProductGradient.m 726B
exampleLInf.m 713B
HuberDataProxDual.m 672B
FrobeniusProxDual.m 657B
L1IsoProxDual.m 641B
constraintBoxDualized.m 632B
printToCmd.m 576B
L2DataProxDual.m 513B
L1DataProxDual.m 510B
huberDataTermOperator.m 493B
nonNegativityConstraintOperator.m 461B
huberOperator.m 445B
L1divAnticurlIso.m 445B
L1curlSwitched.m 444B
L1divCurlIso.m 429B
L1AnisoProxDualShift.m 426B
L1curlPlus.m 422B
L1curl.m 411B
L2dataTermOperator.m 403B
frobeniusOperator.m 401B
L1dataTermOperator.m 399B
L1divergence.m 399B
L1operatorAniso.m 399B
L1shearAniso.m 398B
L2divergence.m 395B
L2curl.m 394B
L1operatorIso.m 393B
L1shearIso.m 392B
L1secondOrderGradientAniso.m 391B
L2operator.m 385B
L1secondOrderGradientIso.m 385B
L2proxDual.m 384B
huberGradient.m 383B
LInfdataTermOperator.m 380B
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