IMPLEMENTATION OF THE VIDEO DENOISING ALGORITHM NON-LOCAL KALMAN

• Author : EHRET Thibaud ehret.thibaud@gmail.com
• Copyright : (C) 2019 IPOL Image Processing On Line http://www.ipol.im/
• Licence : GPL v3+, see gpl.txt

OVERVIEW

This source code provides an implementation of NL-Kalman developped in "Thibaud Ehret, Jean-Michel Morel, Pablo Arias, Non-Local Kalman: a recursive video denoising algorithm ICIP 2018". Video examples are available on the webpage of the article

In order to reproduce the results from the ICIP article a post-processing step consisting of applying DCT denoising is necessary.

The DCT denoising and the TVL1 optical flow codes are provided inside this repo in order to centralize all code necessary to reproduce the results. Shell script linking the different parts are also provided.

This code is part of an IPOL publication. Plase cite it if you use this code as part of your research. (The article is not already published at this time)

COMPILATION

The code is compilable on Unix/Linux and hopefully on Mac OS (not tested!).

Compilation: requires the cmake and make programs.

Dependencies: BLAS, LAPACK and OpenMP [optional]. For image i/o we use Enric Meinhardt's iio, which requires libpng, libtiff and libjpeg.

Compile the source code using make.

UNIX/LINUX/MAC:

$ mkdir build; cd build
$ cmake ..
$ make

Binaries will be created in build/bin folder.

NOTE: By default, the code is compiled with OpenMP multithreaded parallelization enabled (if your system supports it). The number of threads used by the code is defined in nlkalman/nlkalman.h.

USAGE

The following commands have to be run from the current folder:

List all available options:

$ ./nlkalman --help

While being a video denoising algorithm, the method takes as input the frames of the video and not an actual video. The frames can be extracted using ffmpeg on linux. For example:

$ ffmpeg -i video.mp4 video/i%04d.png

There is five mandatory input arguments:

• -i the input sequence
• -of the optical flow corresponding to the input sequence (backward)
• -f the index of the first frame
• -l the index of the last frame
• -sigma the standard deviation of the noise

When providing a sequence that is already noisy the option -add_noise should be set to false.

All path should be given using the C standard. For example to reference to the following video:

• video/i0000.png
• video/i0001.png
• video/i0002.png
• video/i0003.png
• video/i0004.png
• video/i0005.png
• video/i0006.png
• video/i0007.png
• video/i0008.png
• video/i0009.png

The command for denoising with a noise standard deviation of 20 should be

$ ./nlkalman -i video/i%04d.png -f 0 -l 9 -sigma 20 -of video/flow_%04d.flo

AUTOMATED SCRIPT USAGE

/!\ The script has been made for academic purpose. This means that noise is added before any processing. Moreover the PSNR printed at the end is not correct (the PSNR is computed using the noisy data).

Scripts to run the whole pipeline are also provided. The main script is script.sh and is the only one that should be called directly (except if you know what you are doing).

The command to run the pipeline is:

$ ./script.sh inputPath first last sigma sigmaDCT outputPath outputSubPath

where the mandatory inputs are:

• inputPath the path to the input frames (using the C standard), for example 'frame%03d.png'
• first the index of the first frame, for example '1'
• last the index of the last frame, for example '100'
• sigma the noise standard deviation, for example '30'
• sigmaDCT the noise standard deviation for the DCT post-processing (see below) the path to the input frames (using the C standard), for example '6'
• outputPath the path where the output frames will be saved (using the C standard), for example 'output%03d.png'
• outputPathSub the path where the output (subpixelic) frames will be saved (using the C standard), for example 'outputSub%03d.png'

Recommended values for sigmaDCT:

• For sigma=10: sigmaDCT=3
• For sigma=20: sigmaDCT=4
• For sigma=30: sigmaDCT=6

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FILES

This project contains the following source files:

    main function:               src/main_nlkalman.cpp
    command line parsing:        src/cmd_option.h
    nlkalman implementation:     src/nlkalman/nlkalman.h
                                 src/nlkalman/nlkalman.cpp
    parameters container:        src/nlkalman/nlkParams.h
    Matrix operations:           src/nlkalman/LibMatrix.h
                                 src/nlkalman/LibMatrix.cpp
    image i/o:                   src/nlkalman/iio.h
                                 src/nlkalman/iio.c
    image container:             src/nlkalman/LibImages.h
                                 src/nlkalman/LibImages.cpp
    image container:             src/nlkalman/LibVideoT.hpp
                                 src/nlkalman/LibVideoT.cpp
    random number generator:     src/nlkalman/mt19937ar.h
                                 src/nlkalman/mt19937ar.c
    utilities functions:         src/nlkalman/Utilities.h
                                 src/nlkalman/Utilities.cpp
    Parametric trans. functions: src/nlkalman/parametric_transformation.h
                                 src/nlkalman/parametric_transformation.cpp
                                 src/nlkalman/parametric_utils.h
                                 src/nlkalman/parametric_utils.cpp

ABOUT THIS FILE

Copyright 2019 IPOL Image Processing On Line http://www.ipol.im/

Copying and distribution of this file, with or without modification, are permitted in any medium without royalty provided the copyright notice and this notice are preserved. This file is offered as-is, without any warranty.