// run the initilized retina filter in order to perform color tone mapping, after this call all retina outputs are updated
void _runRGBToneMapping(const std::valarray<float> &RGBimageInput, std::valarray<float> &RGBimageOutput, const bool useAdaptiveFiltering)
{
// multiplex the image with the color sampling method specified in the constructor
_colorEngine->runColorMultiplexing(RGBimageInput);
// apply tone mapping on the multiplexed image
_runGrayToneMapping(_colorEngine->getMultiplexedFrame(), RGBimageOutput);
// demultiplex tone maped image
_colorEngine->runColorDemultiplexing(RGBimageOutput, useAdaptiveFiltering, _multiuseFilter->getMaxInputValue());//_ColorEngine->getMultiplexedFrame());//_ParvoRetinaFilter->getPhotoreceptorsLPfilteringOutput());
// rescaling result between 0 and 255
_colorEngine->normalizeRGBOutput_0_maxOutputValue(255.0);
// return the result
RGBimageOutput=_colorEngine->getDemultiplexedColorFrame();
}
/**
* method that applies a luminance correction (initially High Dynamic Range (HDR) tone mapping) using only the 2 local adaptation stages of the retina parvocellular channel : photoreceptors level and ganlion cells level. Spatio temporal filtering is applied but limited to temporal smoothing and eventually high frequencies attenuation. This is a lighter method than the one available using the regular retina::run method. It is then faster but it does not include complete temporal filtering nor retina spectral whitening. Then, it can have a more limited effect on images with a very high dynamic range. This is an adptation of the original still image HDR tone mapping algorithm of David Alleyson, Sabine Susstruck and Laurence Meylan's work, please cite:
* -> Meylan L., Alleysson D., and Susstrunk S., A Model of Retinal Local Adaptation for the Tone Mapping of Color Filter Array Images, Journal of Optical Society of America, A, Vol. 24, N 9, September, 1st, 2007, pp. 2807-2816
@param inputImage the input image to process RGB or gray levels
@param outputToneMappedImage the output tone mapped image
*/
virtual void applyFastToneMapping(InputArray inputImage, OutputArray outputToneMappedImage)
{
// first convert input image to the compatible format :
const bool colorMode = _convertCvMat2ValarrayBuffer(inputImage.getMat(), _inputBuffer);
// process tone mapping
if (colorMode)
{
_runRGBToneMapping(_inputBuffer, _imageOutput, true);
_convertValarrayBuffer2cvMat(_imageOutput, _multiuseFilter->getNBrows(), _multiuseFilter->getNBcolumns(), true, outputToneMappedImage);
}else
{
_runGrayToneMapping(_inputBuffer, _imageOutput);
_convertValarrayBuffer2cvMat(_imageOutput, _multiuseFilter->getNBrows(), _multiuseFilter->getNBcolumns(), false, outputToneMappedImage);
}
}
// run the initilized retina filter in order to perform color tone mapping, after this call all retina outputs are updated
void RetinaFilter::runRGBToneMapping(const std::valarray<float> &RGBimageInput, std::valarray<float> &RGBimageOutput, const bool useAdaptiveFiltering, const float PhotoreceptorsCompression, const float ganglionCellsCompression)
{
// preliminary check
if (!checkInput(RGBimageInput, true))
return;
// multiplex the image with the color sampling method specified in the constructor
_colorEngine.runColorMultiplexing(RGBimageInput);
// apply tone mapping on the multiplexed image
_runGrayToneMapping(_colorEngine.getMultiplexedFrame(), RGBimageOutput, PhotoreceptorsCompression, ganglionCellsCompression);
// demultiplex tone maped image
_colorEngine.runColorDemultiplexing(RGBimageOutput, useAdaptiveFiltering, _photoreceptorsPrefilter.getMaxInputValue());//_ColorEngine->getMultiplexedFrame());//_ParvoRetinaFilter->getPhotoreceptorsLPfilteringOutput());
// rescaling result between 0 and 255
_colorEngine.normalizeRGBOutput_0_maxOutputValue(255.0);
// return the result
RGBimageOutput=_colorEngine.getDemultiplexedColorFrame();
}
