TGV Image Denoising

This code repository is an implementation of the total generalized variation method based on this paper

Platforms

• Linux (Tested)

Requirements

These are the base requirements to build

• Cmake
• A C++17-standard-compliant compiler
• For GPU version you actually need something, that support OpenCL 1.2 (so basically its not always GPU)

Installing

  mkdir build
  cd build
  cmake -D BUILD_RELEASE:BOOL=true ..
  cmake --build .

Running the tests

Compile with Cmake flag -D BUILD_RELEASE:BOOL=false

  mkdir build
  cd build
  cmake -D BUILD_RELEASE:BOOL=false ..
  cmake --build .

How to use

Current solution based on command line interface with keys.

Key	Purpose	Default Value
-c	Use CPU	False
-g	Use GPU	True
-n <Num>	Amount of Iterations	1000
-p <Folder Path>	Path to folder with data	data
-a <Num>	Index of gpu if there are a more than 1	0
-r <File name>	Name of the result file	result
-i <Num>	amount of images for GPU	10
-scaleX <Num>	scale for X axis for Ply file	1.0
-scaleY <Num>	scale for Y axis for Ply file	1.0

So just start program with these keys

File format

Program works with PFM, so perhaps you will have to convert files

Examples

./TGV -g -n 400 -p "data" -a "0" -r "resultFileName" -i 14

./TGV -p "data" -a "0" -r "DenoisedImage" -i 6

Authors

• Daniil Smolyakov - Initial work and CPU/GPU based code - DanonOfficial

License

This project is licensed under the MIT License - see the LICENSE.md file for details