Merge pull request #2399 from elim-dk:algorithm/intensity-transformations

set(the_description "Intensity transformations")

ocv_define_module(intensity_transform opencv_core WRAP python)

Intensity Transformations

========================

This module contains some of the intensity transformation methods used to adjust the constrast of an image. The methods in the module include autoscaling, gamma correction, log transformations, and contrast stretching.

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@book{Gonzalez2018,

  title={Digital Image Processing 4th Edition},

  author={Rafael C. Gonzalez, Richard E. Woods},

  year={2018},

  publisher={Pearson}

}

@misc{lcs435lab,

  title={CS425 Lab: Intensity Transformations and Spatial Filtering},

  url={http://www.cs.uregina.ca/Links/class-info/425/Lab3/}

}

@misc{theailearner,

  title={Contrast Stretching},

  url={https://theailearner.com/2019/01/30/contrast-stretching/}

}

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// This file is part of OpenCV project.

// It is subject to the license terms in the LICENSE file found in the top-level directory

// of this distribution and at http://opencv.org/license.html.

#ifndef OPENCV_INTENSITY_TRANSFORM_H

#define OPENCV_INTENSITY_TRANSFORM_H

#include "opencv2/core.hpp"

/**

 * @defgroup intensity_transform The module brings implementations of intensity transformation algorithms to adjust image contrast.

 *

 * Namespace for all functions is cv::intensity_trasnform.

 *

 * ### Supported Algorithms

 * - Autoscaling

 * - Log Transformations

 * - Power-Law (Gamma) Transformations

 * - Contrast Stretching

 *

 * Reference from following book and websites:

 * - Digital Image Processing 4th Edition Chapter 3 [Rafael C. Gonzalez, Richard E. Woods] @cite Gonzalez2018

 * - http://www.cs.uregina.ca/Links/class-info/425/Lab3/ @cite lcs435lab

 * - https://theailearner.com/2019/01/30/contrast-stretching/ @cite theailearner

*/

namespace cv {

namespace intensity_transform {

//! @addtogroup intensity_transform

//! @{

/**

 * @brief Given an input bgr or grayscale image and constant c, apply log transformation to the image

 * on domain [0, 255] and return the resulting image.

 *

 * @param input input bgr or grayscale image.

 * @param output resulting image of log transformations.

*/

CV_EXPORTS_W void logTransform(const Mat input, Mat& output);

/**

 * @brief Given an input bgr or grayscale image and constant gamma, apply power-law transformation,

 * a.k.a. gamma correction to the image on domain [0, 255] and return the resulting image.

 *

 * @param input input bgr or grayscale image.

 * @param output resulting image of gamma corrections.

 * @param gamma constant in c*r^gamma where r is pixel value.

*/

CV_EXPORTS_W void gammaCorrection(const Mat input, Mat& output, const float gamma);

/**

 * @brief Given an input bgr or grayscale image, apply autoscaling on domain [0, 255] to increase

 * the contrast of the input image and return the resulting image.

 *

 * @param input input bgr or grayscale image.

 * @param output resulting image of autoscaling.

*/

CV_EXPORTS_W void autoscaling(const Mat input, Mat& output);

/**

 * @brief Given an input bgr or grayscale image, apply linear contrast stretching on domain [0, 255]

 * and return the resulting image.

 *

 * @param input input bgr or grayscale image.

 * @param output resulting image of contrast stretching.

 * @param r1 x coordinate of first point (r1, s1) in the transformation function.

 * @param s1 y coordinate of first point (r1, s1) in the transformation function.

 * @param r2 x coordinate of second point (r2, s2) in the transformation function.

 * @param s2 y coordinate of second point (r2, s2) in the transformation function.

*/

CV_EXPORTS_W void contrastStretching(const Mat input, Mat& output, const int r1, const int s1, const int r2, const int s2);

//! @}

}} // cv::intensity_transform::

#endif

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#include "opencv2/core.hpp"

#include "opencv2/imgcodecs.hpp"

#include "opencv2/highgui.hpp"

#include "opencv2/intensity_transform.hpp"

#include <iostream>

using namespace std;

using namespace cv;

using namespace cv::intensity_transform;

int main(int argc, char **argv)

{

    if (argc != 2)

    {

        cerr << "Must input the path of the input image. Ex: intensity_transform image.jpg" << endl;

        return -1;

    }

    // Read input image

    Mat image = imread(argv[1]);

    // Apply intensity transformations

    Mat imgGamma, imgAutoscaled, imgLog, contrastStretch;

    gammaCorrection(image, imgGamma, (float)(0.4));

    autoscaling(image, imgAutoscaled);

    logTransform(image, imgLog);

    contrastStretching(image, contrastStretch, 70, 15, 120, 240);

    // Display intensity transformation results

    imshow("Original Image", image);

    imshow("Autoscale", imgAutoscaled);

    imshow("Gamma Correction", imgGamma);

    imshow("Log Transformation", imgLog);

    imshow("Contrast Stretching", contrastStretch);

    waitKey(0);

    return 0;

}

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