Retina (JavaCPP Presets for OpenCV 4.3.0-1.5.3 API)

java.lang.Object
- org.bytedeco.javacpp.Pointer
- - org.bytedeco.opencv.opencv_core.Algorithm
  - - org.bytedeco.opencv.opencv_bioinspired.Retina

All Implemented Interfaces:

AutoCloseable
```
@Namespace(value="cv::bioinspired")
 @Properties(inherit=opencv_bioinspired.class)
public class Retina
extends Algorithm
```
\brief class which allows the Gipsa/Listic Labs model to be used with OpenCV.
This retina model allows spatio-temporal image processing (applied on still images, video sequences). As a summary, these are the retina model properties: - It applies a spectral whithening (mid-frequency details enhancement) - high frequency spatio-temporal noise reduction - low frequency luminance to be reduced (luminance range compression) - local logarithmic luminance compression allows details to be enhanced in low light conditions
USE : this model can be used basically for spatio-temporal video effects but also for : _using the getParvo method output matrix : texture analysiswith enhanced signal to noise ratio and enhanced details robust against input images luminance ranges _using the getMagno method output matrix : motion analysis also with the previously cited properties
for more information, reer to the following papers : Benoit A., Caplier A., Durette B., Herault, J., "USING HUMAN VISUAL SYSTEM MODELING FOR BIO-INSPIRED LOW LEVEL IMAGE PROCESSING", Elsevier, Computer Vision and Image Understanding 114 (2010), pp. 758-773, DOI: http://dx.doi.org/10.1016/j.cviu.2010.01.011 Vision: Images, Signals and Neural Networks: Models of Neural Processing in Visual Perception (Progress in Neural Processing),By: Jeanny Herault, ISBN: 9814273686. WAPI (Tower ID): 113266891.
The retina filter includes the research contributions of phd/research collegues from which code has been redrawn by the author : take a look at the retinacolor.hpp module to discover Brice Chaix de Lavarene color mosaicing/demosaicing and the reference paper: B. Chaix de Lavarene, D. Alleysson, B. Durette, J. Herault (2007). "Efficient demosaicing through recursive filtering", IEEE International Conference on Image Processing ICIP 2007 take a look at imagelogpolprojection.hpp to discover retina spatial log sampling which originates from Barthelemy Durette phd with Jeanny Herault. A Retina / V1 cortex projection is also proposed and originates from Jeanny's discussions. more informations in the above cited Jeanny Heraults's book.

Nested Class Summary
- Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer
  Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter

Field Summary
- Fields inherited from class org.bytedeco.javacpp.Pointer
  address, capacity, limit, position

Constructor Summary

Constructors
Constructor and Description

Retina(Pointer p)
Pointer cast constructor.

Constructors
Constructor and Description
`Retina(Pointer p)` Pointer cast constructor.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`activateContoursProcessing(boolean activate)` \brief Activate/desactivate the Parvocellular pathway processing (contours information extraction), by default, it is activated
`void`	`activateMovingContoursProcessing(boolean activate)` \brief Activate/desactivate the Magnocellular pathway processing (motion information extraction), by default, it is activated
`void`	`applyFastToneMapping(GpuMat inputImage, GpuMat outputToneMappedImage)`
`void`	`applyFastToneMapping(Mat inputImage, Mat outputToneMappedImage)` \brief Method which processes an image in the aim to correct its luminance correct backlight problems, enhance details in shadows.
`void`	`applyFastToneMapping(UMat inputImage, UMat outputToneMappedImage)`
`void`	`clearBuffers()` \brief Clears all retina buffers
`static Retina`	`create(Size inputSize)` \overload
`static Retina`	`create(Size inputSize, boolean colorMode)`
`static Retina`	`create(Size inputSize, boolean colorMode, int colorSamplingMethod, boolean useRetinaLogSampling, float reductionFactor, float samplingStrength)` \brief Constructors from standardized interfaces : retreive a smart pointer to a Retina instance
`Size`	`getInputSize()` \brief Retreive retina input buffer size
`void`	`getMagno(GpuMat retinaOutput_magno)`
`void`	`getMagno(Mat retinaOutput_magno)` \brief Accessor of the motion channel of the retina (models peripheral vision).
`void`	`getMagno(UMat retinaOutput_magno)`
`Mat`	`getMagnoRAW()` \overload
`void`	`getMagnoRAW(GpuMat retinaOutput_magno)`
`void`	`getMagnoRAW(Mat retinaOutput_magno)` \brief Accessor of the motion channel of the retina (models peripheral vision).
`void`	`getMagnoRAW(UMat retinaOutput_magno)`
`Size`	`getOutputSize()` \brief Retreive retina output buffer size that can be different from the input if a spatial log transformation is applied
`RetinaParameters`	`getParameters()`
`void`	`getParvo(GpuMat retinaOutput_parvo)`
`void`	`getParvo(Mat retinaOutput_parvo)` \brief Accessor of the details channel of the retina (models foveal vision).
`void`	`getParvo(UMat retinaOutput_parvo)`
`Mat`	`getParvoRAW()` \overload
`void`	`getParvoRAW(GpuMat retinaOutput_parvo)`
`void`	`getParvoRAW(Mat retinaOutput_parvo)` \brief Accessor of the details channel of the retina (models foveal vision).
`void`	`getParvoRAW(UMat retinaOutput_parvo)`
`BytePointer`	`printSetup()` \brief Outputs a string showing the used parameters setup
`void`	`run(GpuMat inputImage)`
`void`	`run(Mat inputImage)` \brief Method which allows retina to be applied on an input image,
`void`	`run(UMat inputImage)`
`void`	`setColorSaturation()`
`void`	`setColorSaturation(boolean saturateColors, float colorSaturationValue)` \brief Activate color saturation as the final step of the color demultiplexing process -\> this saturation is a sigmoide function applied to each channel of the demultiplexed image.
`void`	`setup()`
`void`	`setup(BytePointer retinaParameterFile, boolean applyDefaultSetupOnFailure)` \brief Try to open an XML retina parameters file to adjust current retina instance setup
`void`	`setup(FileStorage fs)`
`void`	`setup(FileStorage fs, boolean applyDefaultSetupOnFailure)` \overload
`void`	`setup(RetinaParameters newParameters)` \overload
`void`	`setup(String retinaParameterFile, boolean applyDefaultSetupOnFailure)`
`void`	`setupIPLMagnoChannel()`
`void`	`setupIPLMagnoChannel(boolean normaliseOutput, float parasolCells_beta, float parasolCells_tau, float parasolCells_k, float amacrinCellsTemporalCutFrequency, float V0CompressionParameter, float localAdaptintegration_tau, float localAdaptintegration_k)` \brief Set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel
`void`	`setupOPLandIPLParvoChannel()`
`void`	`setupOPLandIPLParvoChannel(boolean colorMode, boolean normaliseOutput, float photoreceptorsLocalAdaptationSensitivity, float photoreceptorsTemporalConstant, float photoreceptorsSpatialConstant, float horizontalCellsGain, float HcellsTemporalConstant, float HcellsSpatialConstant, float ganglionCellsSensitivity)` \brief Setup the OPL and IPL parvo channels (see biologocal model)
`void`	`write(BytePointer fs)` \brief Write xml/yml formated parameters information
`void`	`write(FileStorage fs)` \overload
`void`	`write(String fs)`

Methods inherited from class org.bytedeco.opencv.opencv_core.Algorithm
clear, empty, getDefaultName, position, read, save, save, write, write

Methods inherited from class org.bytedeco.javacpp.Pointer
address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - Retina
```
public Retina(Pointer p)
```
    Pointer cast constructor. Invokes Pointer.Pointer(Pointer).
- Method Detail
  - getInputSize
```
@ByVal
public Size getInputSize()
```
    \brief Retreive retina input buffer size
    
    Returns:
    
    the retina input buffer size
  - getOutputSize
```
@ByVal
public Size getOutputSize()
```
    \brief Retreive retina output buffer size that can be different from the input if a spatial log transformation is applied
    
    Returns:
    
    the retina output buffer size
  - setup
```
public void setup(@opencv_core.Str
                  BytePointer retinaParameterFile,
                  @Cast(value="const bool")
                  boolean applyDefaultSetupOnFailure)
```
    \brief Try to open an XML retina parameters file to adjust current retina instance setup
    - if the xml file does not exist, then default setup is applied - warning, Exceptions are thrown if read XML file is not valid
    
    Parameters:
    
    retinaParameterFile - the parameters filename
    
    applyDefaultSetupOnFailure - set to true if an error must be thrown on error
    You can retrieve the current parameters structure using the method Retina::getParameters and update it before running method Retina::setup.
  - setup
```
public void setup()
```
  - setup
```
public void setup(@opencv_core.Str
                  String retinaParameterFile,
                  @Cast(value="const bool")
                  boolean applyDefaultSetupOnFailure)
```
  - setup
```
public void setup(@ByRef
                  FileStorage fs,
                  @Cast(value="const bool")
                  boolean applyDefaultSetupOnFailure)
```
    \overload
    
    Parameters:
    
    fs - the open Filestorage which contains retina parameters
    
    applyDefaultSetupOnFailure - set to true if an error must be thrown on error
  - setup
```
public void setup(@ByRef
                  FileStorage fs)
```
  - setup
```
public void setup(@ByVal
                  RetinaParameters newParameters)
```
    \overload
    
    Parameters:
    
    newParameters - a parameters structures updated with the new target configuration.
  - getParameters
```
@ByVal
public RetinaParameters getParameters()
```
    Returns:
    
    the current parameters setup
  - printSetup
```
@opencv_core.Str
public BytePointer printSetup()
```
    \brief Outputs a string showing the used parameters setup
    
    Returns:
    
    a string which contains formated parameters information
  - write
```
public void write(@opencv_core.Str
                  BytePointer fs)
```
    \brief Write xml/yml formated parameters information
    
    Parameters:
    
    fs - the filename of the xml file that will be open and writen with formatted parameters information
  - write
```
public void write(@opencv_core.Str
                  String fs)
```
  - write
```
public void write(@ByRef
                  FileStorage fs)
```
    \overload
    
    Overrides:
    
    write in class Algorithm
  - setupOPLandIPLParvoChannel
```
public void setupOPLandIPLParvoChannel(@Cast(value="const bool")
                                       boolean colorMode,
                                       @Cast(value="const bool")
                                       boolean normaliseOutput,
                                       float photoreceptorsLocalAdaptationSensitivity,
                                       float photoreceptorsTemporalConstant,
                                       float photoreceptorsSpatialConstant,
                                       float horizontalCellsGain,
                                       float HcellsTemporalConstant,
                                       float HcellsSpatialConstant,
                                       float ganglionCellsSensitivity)
```
    \brief Setup the OPL and IPL parvo channels (see biologocal model)
    OPL is referred as Outer Plexiform Layer of the retina, it allows the spatio-temporal filtering which withens the spectrum and reduces spatio-temporal noise while attenuating global luminance (low frequency energy) IPL parvo is the OPL next processing stage, it refers to a part of the Inner Plexiform layer of the retina, it allows high contours sensitivity in foveal vision. See reference papers for more informations. for more informations, please have a look at the paper Benoit A., Caplier A., Durette B., Herault, J., "USING HUMAN VISUAL SYSTEM MODELING FOR BIO-INSPIRED LOW LEVEL IMAGE PROCESSING", Elsevier, Computer Vision and Image Understanding 114 (2010), pp. 758-773, DOI: http://dx.doi.org/10.1016/j.cviu.2010.01.011
    
    Parameters:
    
    colorMode - specifies if (true) color is processed of not (false) to then processing gray level image
    
    normaliseOutput - specifies if (true) output is rescaled between 0 and 255 of not (false)
    
    photoreceptorsLocalAdaptationSensitivity - the photoreceptors sensitivity renage is 0-1 (more log compression effect when value increases)
    
    photoreceptorsTemporalConstant - the time constant of the first order low pass filter of the photoreceptors, use it to cut high temporal frequencies (noise or fast motion), unit is frames, typical value is 1 frame
    
    photoreceptorsSpatialConstant - the spatial constant of the first order low pass filter of the photoreceptors, use it to cut high spatial frequencies (noise or thick contours), unit is pixels, typical value is 1 pixel
    
    horizontalCellsGain - gain of the horizontal cells network, if 0, then the mean value of the output is zero, if the parameter is near 1, then, the luminance is not filtered and is still reachable at the output, typicall value is 0
    
    HcellsTemporalConstant - the time constant of the first order low pass filter of the horizontal cells, use it to cut low temporal frequencies (local luminance variations), unit is frames, typical value is 1 frame, as the photoreceptors
    
    HcellsSpatialConstant - the spatial constant of the first order low pass filter of the horizontal cells, use it to cut low spatial frequencies (local luminance), unit is pixels, typical value is 5 pixel, this value is also used for local contrast computing when computing the local contrast adaptation at the ganglion cells level (Inner Plexiform Layer parvocellular channel model)
    
    ganglionCellsSensitivity - the compression strengh of the ganglion cells local adaptation output, set a value between 0.6 and 1 for best results, a high value increases more the low value sensitivity... and the output saturates faster, recommended value: 0.7
  - setupOPLandIPLParvoChannel
```
public void setupOPLandIPLParvoChannel()
```
  - setupIPLMagnoChannel
```
public void setupIPLMagnoChannel(@Cast(value="const bool")
                                 boolean normaliseOutput,
                                 float parasolCells_beta,
                                 float parasolCells_tau,
                                 float parasolCells_k,
                                 float amacrinCellsTemporalCutFrequency,
                                 float V0CompressionParameter,
                                 float localAdaptintegration_tau,
                                 float localAdaptintegration_k)
```
    \brief Set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel
    this channel processes signals output from OPL processing stage in peripheral vision, it allows motion information enhancement. It is decorrelated from the details channel. See reference papers for more details.
    
    Parameters:
    
    normaliseOutput - specifies if (true) output is rescaled between 0 and 255 of not (false)
    
    parasolCells_beta - the low pass filter gain used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), typical value is 0
    
    parasolCells_tau - the low pass filter time constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is frame, typical value is 0 (immediate response)
    
    parasolCells_k - the low pass filter spatial constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is pixels, typical value is 5
    
    amacrinCellsTemporalCutFrequency - the time constant of the first order high pass fiter of the magnocellular way (motion information channel), unit is frames, typical value is 1.2
    
    V0CompressionParameter - the compression strengh of the ganglion cells local adaptation output, set a value between 0.6 and 1 for best results, a high value increases more the low value sensitivity... and the output saturates faster, recommended value: 0.95
    
    localAdaptintegration_tau - specifies the temporal constant of the low pas filter involved in the computation of the local "motion mean" for the local adaptation computation
    
    localAdaptintegration_k - specifies the spatial constant of the low pas filter involved in the computation of the local "motion mean" for the local adaptation computation
  - setupIPLMagnoChannel
```
public void setupIPLMagnoChannel()
```
  - run
```
public void run(@ByVal
                Mat inputImage)
```
    \brief Method which allows retina to be applied on an input image,
    after run, encapsulated retina module is ready to deliver its outputs using dedicated acccessors, see getParvo and getMagno methods
    
    Parameters:
    
    inputImage - the input Mat image to be processed, can be gray level or BGR coded in any format (from 8bit to 16bits)
  - run
```
public void run(@ByVal
                UMat inputImage)
```
  - run
```
public void run(@ByVal
                GpuMat inputImage)
```
  - applyFastToneMapping
```
public void applyFastToneMapping(@ByVal
                                 Mat inputImage,
                                 @ByVal
                                 Mat outputToneMappedImage)
```
    \brief Method which processes an image in the aim to correct its luminance correct backlight problems, enhance details in shadows.
    This method is designed to perform High Dynamic Range image tone mapping (compress \>8bit/pixel images to 8bit/pixel). This is a simplified version of the Retina Parvocellular model (simplified version of the run/getParvo methods call) since it does not include the spatio-temporal filter modelling the Outer Plexiform Layer of the retina that performs spectral whitening and many other stuff. However, it works great for tone mapping and in a faster way.
    Check the demos and experiments section to see examples and the way to perform tone mapping using the original retina model and the method.
    
    Parameters:
    
    inputImage - the input image to process (should be coded in float format : CV_32F, CV_32FC1, CV_32F_C3, CV_32F_C4, the 4th channel won't be considered).
    
    outputToneMappedImage - the output 8bit/channel tone mapped image (CV_8U or CV_8UC3 format).
  - applyFastToneMapping
```
public void applyFastToneMapping(@ByVal
                                 UMat inputImage,
                                 @ByVal
                                 UMat outputToneMappedImage)
```
  - applyFastToneMapping
```
public void applyFastToneMapping(@ByVal
                                 GpuMat inputImage,
                                 @ByVal
                                 GpuMat outputToneMappedImage)
```
  - getParvo
```
public void getParvo(@ByVal
                     Mat retinaOutput_parvo)
```
    \brief Accessor of the details channel of the retina (models foveal vision).
    Warning, getParvoRAW methods return buffers that are not rescaled within range [0;255] while the non RAW method allows a normalized matrix to be retrieved.
    
    Parameters:
    
    retinaOutput_parvo - the output buffer (reallocated if necessary), format can be : - a Mat, this output is rescaled for standard 8bits image processing use in OpenCV - RAW methods actually return a 1D matrix (encoding is R1, R2, ... Rn, G1, G2, ..., Gn, B1, B2, ...Bn), this output is the original retina filter model output, without any quantification or rescaling.
    
    See Also:
    
    getParvoRAW
  - getParvo
```
public void getParvo(@ByVal
                     UMat retinaOutput_parvo)
```
  - getParvo
```
public void getParvo(@ByVal
                     GpuMat retinaOutput_parvo)
```
  - getParvoRAW
```
public void getParvoRAW(@ByVal
                        Mat retinaOutput_parvo)
```
    \brief Accessor of the details channel of the retina (models foveal vision).
    
    See Also:
    
    getParvo
  - getParvoRAW
```
public void getParvoRAW(@ByVal
                        UMat retinaOutput_parvo)
```
  - getParvoRAW
```
public void getParvoRAW(@ByVal
                        GpuMat retinaOutput_parvo)
```
  - getMagno
```
public void getMagno(@ByVal
                     Mat retinaOutput_magno)
```
    \brief Accessor of the motion channel of the retina (models peripheral vision).
    Warning, getMagnoRAW methods return buffers that are not rescaled within range [0;255] while the non RAW method allows a normalized matrix to be retrieved.
    
    Parameters:
    
    retinaOutput_magno - the output buffer (reallocated if necessary), format can be : - a Mat, this output is rescaled for standard 8bits image processing use in OpenCV - RAW methods actually return a 1D matrix (encoding is M1, M2,... Mn), this output is the original retina filter model output, without any quantification or rescaling.
    
    See Also:
    
    getMagnoRAW
  - getMagno
```
public void getMagno(@ByVal
                     UMat retinaOutput_magno)
```
  - getMagno
```
public void getMagno(@ByVal
                     GpuMat retinaOutput_magno)
```
  - getMagnoRAW
```
public void getMagnoRAW(@ByVal
                        Mat retinaOutput_magno)
```
    \brief Accessor of the motion channel of the retina (models peripheral vision).
    
    See Also:
    
    getMagno
  - getMagnoRAW
```
public void getMagnoRAW(@ByVal
                        UMat retinaOutput_magno)
```
  - getMagnoRAW
```
public void getMagnoRAW(@ByVal
                        GpuMat retinaOutput_magno)
```
  - getMagnoRAW
```
@Const
 @ByVal
public Mat getMagnoRAW()
```
    \overload
  - getParvoRAW
```
@Const
 @ByVal
public Mat getParvoRAW()
```
    \overload
  - setColorSaturation
```
public void setColorSaturation(@Cast(value="const bool")
                               boolean saturateColors,
                               float colorSaturationValue)
```
    \brief Activate color saturation as the final step of the color demultiplexing process -\> this saturation is a sigmoide function applied to each channel of the demultiplexed image.
    
    Parameters:
    
    saturateColors - boolean that activates color saturation (if true) or desactivate (if false)
    
    colorSaturationValue - the saturation factor : a simple factor applied on the chrominance buffers
  - setColorSaturation
```
public void setColorSaturation()
```
  - clearBuffers
```
public void clearBuffers()
```
    \brief Clears all retina buffers
    (equivalent to opening the eyes after a long period of eye close ;o) whatchout the temporal transition occuring just after this method call.
  - activateMovingContoursProcessing
```
public void activateMovingContoursProcessing(@Cast(value="const bool")
                                             boolean activate)
```
    \brief Activate/desactivate the Magnocellular pathway processing (motion information extraction), by default, it is activated
    
    Parameters:
    
    activate - true if Magnocellular output should be activated, false if not... if activated, the Magnocellular output can be retrieved using the **getMagno** methods
  - activateContoursProcessing
```
public void activateContoursProcessing(@Cast(value="const bool")
                                       boolean activate)
```
    \brief Activate/desactivate the Parvocellular pathway processing (contours information extraction), by default, it is activated
    
    Parameters:
    
    activate - true if Parvocellular (contours information extraction) output should be activated, false if not... if activated, the Parvocellular output can be retrieved using the Retina::getParvo methods
  - create
```
@opencv_core.Ptr
public static Retina create(@ByVal
                                             Size inputSize)
```
    \overload
  - create
```
@opencv_core.Ptr
public static Retina create(@ByVal
                                             Size inputSize,
                                             @Cast(value="const bool")
                                             boolean colorMode,
                                             int colorSamplingMethod,
                                             @Cast(value="const bool")
                                             boolean useRetinaLogSampling,
                                             float reductionFactor,
                                             float samplingStrength)
```
    \brief Constructors from standardized interfaces : retreive a smart pointer to a Retina instance
    
    Parameters:
    
    inputSize - the input frame size
    
    colorMode - the chosen processing mode : with or without color processing
    
    colorSamplingMethod - specifies which kind of color sampling will be used : - cv::bioinspired::RETINA_COLOR_RANDOM: each pixel position is either R, G or B in a random choice - cv::bioinspired::RETINA_COLOR_DIAGONAL: color sampling is RGBRGBRGB..., line 2 BRGBRGBRG..., line 3, GBRGBRGBR... - cv::bioinspired::RETINA_COLOR_BAYER: standard bayer sampling
    
    useRetinaLogSampling - activate retina log sampling, if true, the 2 following parameters can be used
    
    reductionFactor - only usefull if param useRetinaLogSampling=true, specifies the reduction factor of the output frame (as the center (fovea) is high resolution and corners can be underscaled, then a reduction of the output is allowed without precision leak
    
    samplingStrength - only usefull if param useRetinaLogSampling=true, specifies the strength of the log scale that is applied
  - create
```
@opencv_core.Ptr
public static Retina create(@ByVal
                                             Size inputSize,
                                             @Cast(value="const bool")
                                             boolean colorMode)
```

Class Retina

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

Constructor Summary

Method Summary

Methods inherited from class org.bytedeco.opencv.opencv_core.Algorithm

Methods inherited from class org.bytedeco.javacpp.Pointer

Methods inherited from class java.lang.Object

Constructor Detail

Retina

Method Detail

getInputSize

getOutputSize

setup

setup

setup

setup

setup

setup

getParameters

printSetup

write

write

write

setupOPLandIPLParvoChannel

setupOPLandIPLParvoChannel

setupIPLMagnoChannel

setupIPLMagnoChannel

run

run

run

applyFastToneMapping

applyFastToneMapping

applyFastToneMapping

getParvo

getParvo

getParvo

getParvoRAW

getParvoRAW

getParvoRAW

getMagno

getMagno

getMagno

getMagnoRAW

getMagnoRAW

getMagnoRAW

getMagnoRAW

getParvoRAW

setColorSaturation

setColorSaturation

clearBuffers

activateMovingContoursProcessing

activateContoursProcessing

create

create

create