Deleting old tutorial files and put them in folders

doc/tutorials/ImgProc/Basic_Linear_Transforms/Basic_Linear_Transform.rst

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+.. _Basic_Linear_Transform:
+
+Changing the contrast and brightness of an image!
+***************************************************
+
+Goal
+=====
+
+In this tutorial you will learn how to:
+
+* Access pixel values 
+
+* Initialize a matrix with zeros
+
+* Learn what :saturate_cast:`saturate_cast <>` does and why it is useful
+
+* Get some cool info about pixel transformations
+
+Cool Theory
+=================
+ 
+.. note::
+   The explanation below belongs to the book `Computer Vision: Algorithms and Applications <http://szeliski.org/Book/>`_  by Richard Szeliski 
+
+Image Processing
+--------------------
+
+* A general image processing operator is a function that takes one or more input images and produces an output image. 
+
+* Image transforms can be seen as:
+
+  * Point operators (pixel transforms)
+  * Neighborhood (area-based) operators
+
+
+Pixel Transforms
+^^^^^^^^^^^^^^^^^
+
+* In this kind of image processing transform, each output pixel's value depends on only the corresponding input pixel value (plus, potentially, some globally collected information or parameters).
+
+* Examples of such operators include *brightness and contrast adjustments* as well as color correction and transformations.
+
+Brightness and contrast adjustments
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+* Two commonly used point processes are *multiplication* and *addition* with a constant:
+
+  .. math::
+
+     g(x) = \alpha f(x) + \beta
+
+* The parameters :math:`\alpha > 0` and :math:`\beta` are often called the *gain* and *bias* parameters; sometimes these parameters are said to control *contrast* and *brightness* respectively.
+
+* You can think of :math:`f(x)` as the source image pixels and :math:`g(x)` as the output image pixels. Then, more conveniently we can write the expression as:
+
+  .. math::
+   
+     g(i,j) = \alpha \cdot f(i,j) + \beta
+  where :math:`i` and :math:`j` indicates that the pixel is located in the *i-th* row and *j-th* column. 
+
+Code
+=====
+
+* The following code performs the operation :math:`g(i,j) = \alpha \cdot f(i,j) + \beta`
+* Here it is:
+
+.. code-block:: cpp
+
+   #include <cv.h>
+   #include <highgui.h>
+   #include <iostream>
+
+   using namespace cv;
+
+   double alpha; /**< Simple contrast control */
+   int beta;  /**< Simple brightness control */
+
+   int main( int argc, char** argv )
+   {
+    /// Read image given by user
+    Mat image = imread( argv[1] );
+    Mat new_image = Mat::zeros( image.size(), image.type() );
+
+    /// Initialize values 
+    std::cout<<" Basic Linear Transforms "<<std::endl;
+    std::cout<<"-------------------------"<<std::endl;
+    std::cout<<"* Enter the alpha value [1.0-3.0]: ";std::cin>>alpha;
+    std::cout<<"* Enter the beta value [0-100]: "; std::cin>>beta;
+
+    /// Do the operation new_image(i,j) = alpha*image(i,j) + beta
+    for( int y = 0; y < image.rows; y++ )
+       { for( int x = 0; x < image.cols; x++ )
+            { for( int c = 0; c < 3; c++ )
+                 {
+		  new_image.at<Vec3b>(y,x)[c] = saturate_cast<uchar>( alpha*( image.at<Vec3b>(y,x)[c] ) + beta );
+                }
+	    }
+       }
+
+    /// Create Windows
+    namedWindow("Original Image", 1);
+    namedWindow("New Image", 1);
+
+    /// Show stuff
+    imshow("Original Image", image);
+    imshow("New Image", new_image);
+
+    /// Wait until user press some key
+    waitKey();
+    return 0;
+   }
+
+Explanation
+============
+
+#. We begin by creating parameters to save :math:`\alpha` and :math:`\beta` to be entered by the user:
+
+   .. code-block:: cpp
+
+      double alpha;
+      int beta;
+
+
+#. We load an image using :imread:`imread <>` and save it in a Mat object:
+   
+   .. code-block:: cpp
+
+      Mat image = imread( argv[1] );
+
+#. Now, since we will make some transformations to this image, we need a new Mat object to store it. Also, we want this to have the following features:
+   
+   * Initial pixel values equal to zero
+   * Same size and type as the original image
+ 
+   .. code-block:: cpp
+
+      Mat new_image = Mat::zeros( image.size(), image.type() ); 
+ 
+   We observe that :mat_zeros:`Mat::zeros <>` returns a Matlab-style zero initializer based on *image.size()* and *image.type()*  
+
+#. Now, to perform the operation :math:`g(i,j) = \alpha \cdot f(i,j) + \beta` we will access to each pixel in image. Since we are operating with RGB images, we will have three values per pixel (R, G and B), so we will also access them separately. Here is the piece of code:
+
+   .. code-block:: cpp
+ 
+      for( int y = 0; y < image.rows; y++ )
+         { for( int x = 0; x < image.cols; x++ )
+              { for( int c = 0; c < 3; c++ )
+                   { new_image.at<Vec3b>(y,x)[c] = saturate_cast<uchar>( alpha*( image.at<Vec3b>(y,x)[c] ) + beta ); }
+	      }
+         }
+ 
+   Notice the following:
+
+   * To access each pixel in the images we are using this syntax: *image.at<Vec3b>(y,x)[c]* where *y* is the row, *x* is the column and *c* is R, G or B (0, 1 or 2). 
+
+   * Since the operation :math:`\alpha \cdot p(i,j) + \beta` can give values out of range or not integers (if :math:`\alpha` is float), we use :saturate_cast:`saturate_cast <>` to make sure the values are valid.
+
+
+#. Finally, we create windows and show the images, the usual way.
+
+   .. code-block:: cpp
+   
+      namedWindow("Original Image", 1);
+      namedWindow("New Image", 1);
+
+      imshow("Original Image", image);
+      imshow("New Image", new_image);
+
+      waitKey(0);
+
+.. note::
+  
+   Instead of using the **for** loops to access each pixel, we could have simply used this command:
+  
+   .. code-block:: cpp
+
+      image.convertTo(new_image, -1, alpha, beta);
+
+   where :convert_to:`convertTo <>` would effectively perform *new_image = a*image + beta*. However, we wanted to show you how to access each pixel. In any case, both methods give the same result.
+
+Result
+=======
+
+* Running our code and using :math:`\alpha = 2.2` and :math:`\beta = 50`
+
+  .. code-block:: bash
+
+     $ ./BasicLinearTransforms lena.png
+     Basic Linear Transforms
+     -------------------------
+     * Enter the alpha value [1.0-3.0]: 2.2
+     * Enter the beta value [0-100]: 50
+
+* We get this:
+
+.. image:: images/Basic_Linear_Transform_Tutorial_Result_0.png
+   :height: 400px
+   :alt: Basic Linear Transform - Final Result
+   :align: center