using OpenCVForUnity.CoreModule;
using OpenCVForUnity.UtilsModule;
using System;
using System.Collections.Generic;
using System.Runtime.InteropServices;
namespace OpenCVForUnity.BioinspiredModule
{
// C++: class RetinaFastToneMapping
/**
* a wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV.
*
* This algorithm is already implemented in thre Retina class (retina::applyFastToneMapping) but used it does not require all the retina model to be allocated. This allows a light memory use for low memory devices (smartphones, etc.
* As a summary, these are the model properties:
*
* -
* 2 stages of local luminance adaptation with a different local neighborhood for each.
*
* -
* first stage models the retina photorecetors local luminance adaptation
*
* -
* second stage models th ganglion cells local information adaptation
*
* -
* compared to the initial publication, this class uses spatio-temporal low pass filters instead of spatial only filters.
* this can help noise robustness and temporal stability for video sequence use cases.
*
*
*
* for more information, read to the following papers :
* 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. 2807-2816Benoit 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
* regarding spatio-temporal filter and the bigger retina model :
* 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.
*/
public class RetinaFastToneMapping : Algorithm
{
protected override void Dispose(bool disposing)
{
try
{
if (disposing)
{
}
if (IsEnabledDispose)
{
if (nativeObj != IntPtr.Zero)
bioinspired_RetinaFastToneMapping_delete(nativeObj);
nativeObj = IntPtr.Zero;
}
}
finally
{
base.Dispose(disposing);
}
}
protected internal RetinaFastToneMapping(IntPtr addr) : base(addr) { }
// internal usage only
public static new RetinaFastToneMapping __fromPtr__(IntPtr addr) { return new RetinaFastToneMapping(addr); }
//
// C++: void cv::bioinspired::RetinaFastToneMapping::applyFastToneMapping(Mat inputImage, Mat& outputToneMappedImage)
//
/**
* 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
*/
public void applyFastToneMapping(Mat inputImage, Mat outputToneMappedImage)
{
ThrowIfDisposed();
if (inputImage != null) inputImage.ThrowIfDisposed();
if (outputToneMappedImage != null) outputToneMappedImage.ThrowIfDisposed();
bioinspired_RetinaFastToneMapping_applyFastToneMapping_10(nativeObj, inputImage.nativeObj, outputToneMappedImage.nativeObj);
}
//
// C++: void cv::bioinspired::RetinaFastToneMapping::setup(float photoreceptorsNeighborhoodRadius = 3.f, float ganglioncellsNeighborhoodRadius = 1.f, float meanLuminanceModulatorK = 1.f)
//
/**
* updates tone mapping behaviors by adjusing the local luminance computation area
*
* param photoreceptorsNeighborhoodRadius the first stage local adaptation area
* param ganglioncellsNeighborhoodRadius the second stage local adaptation area
* param meanLuminanceModulatorK the factor applied to modulate the meanLuminance information
* (default is 1, see reference paper)
*/
public void setup(float photoreceptorsNeighborhoodRadius, float ganglioncellsNeighborhoodRadius, float meanLuminanceModulatorK)
{
ThrowIfDisposed();
bioinspired_RetinaFastToneMapping_setup_10(nativeObj, photoreceptorsNeighborhoodRadius, ganglioncellsNeighborhoodRadius, meanLuminanceModulatorK);
}
/**
* updates tone mapping behaviors by adjusing the local luminance computation area
*
* param photoreceptorsNeighborhoodRadius the first stage local adaptation area
* param ganglioncellsNeighborhoodRadius the second stage local adaptation area
* (default is 1, see reference paper)
*/
public void setup(float photoreceptorsNeighborhoodRadius, float ganglioncellsNeighborhoodRadius)
{
ThrowIfDisposed();
bioinspired_RetinaFastToneMapping_setup_11(nativeObj, photoreceptorsNeighborhoodRadius, ganglioncellsNeighborhoodRadius);
}
/**
* updates tone mapping behaviors by adjusing the local luminance computation area
*
* param photoreceptorsNeighborhoodRadius the first stage local adaptation area
* (default is 1, see reference paper)
*/
public void setup(float photoreceptorsNeighborhoodRadius)
{
ThrowIfDisposed();
bioinspired_RetinaFastToneMapping_setup_12(nativeObj, photoreceptorsNeighborhoodRadius);
}
/**
* updates tone mapping behaviors by adjusing the local luminance computation area
*
* (default is 1, see reference paper)
*/
public void setup()
{
ThrowIfDisposed();
bioinspired_RetinaFastToneMapping_setup_13(nativeObj);
}
//
// C++: static Ptr_RetinaFastToneMapping cv::bioinspired::RetinaFastToneMapping::create(Size inputSize)
//
public static RetinaFastToneMapping create(Size inputSize)
{
return RetinaFastToneMapping.__fromPtr__(DisposableObject.ThrowIfNullIntPtr(bioinspired_RetinaFastToneMapping_create_10(inputSize.width, inputSize.height)));
}
#if (UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR
const string LIBNAME = "__Internal";
#else
const string LIBNAME = "opencvforunity";
#endif
// C++: void cv::bioinspired::RetinaFastToneMapping::applyFastToneMapping(Mat inputImage, Mat& outputToneMappedImage)
[DllImport(LIBNAME)]
private static extern void bioinspired_RetinaFastToneMapping_applyFastToneMapping_10(IntPtr nativeObj, IntPtr inputImage_nativeObj, IntPtr outputToneMappedImage_nativeObj);
// C++: void cv::bioinspired::RetinaFastToneMapping::setup(float photoreceptorsNeighborhoodRadius = 3.f, float ganglioncellsNeighborhoodRadius = 1.f, float meanLuminanceModulatorK = 1.f)
[DllImport(LIBNAME)]
private static extern void bioinspired_RetinaFastToneMapping_setup_10(IntPtr nativeObj, float photoreceptorsNeighborhoodRadius, float ganglioncellsNeighborhoodRadius, float meanLuminanceModulatorK);
[DllImport(LIBNAME)]
private static extern void bioinspired_RetinaFastToneMapping_setup_11(IntPtr nativeObj, float photoreceptorsNeighborhoodRadius, float ganglioncellsNeighborhoodRadius);
[DllImport(LIBNAME)]
private static extern void bioinspired_RetinaFastToneMapping_setup_12(IntPtr nativeObj, float photoreceptorsNeighborhoodRadius);
[DllImport(LIBNAME)]
private static extern void bioinspired_RetinaFastToneMapping_setup_13(IntPtr nativeObj);
// C++: static Ptr_RetinaFastToneMapping cv::bioinspired::RetinaFastToneMapping::create(Size inputSize)
[DllImport(LIBNAME)]
private static extern IntPtr bioinspired_RetinaFastToneMapping_create_10(double inputSize_width, double inputSize_height);
// native support for java finalize()
[DllImport(LIBNAME)]
private static extern void bioinspired_RetinaFastToneMapping_delete(IntPtr nativeObj);
}
}