Documentation improvement for the Stereo module.

Emgu.CV.Contrib/Quality/QualitySSIM.cs

@@ -41,7 +41,7 @@ public IntPtr AlgorithmPtr
         /// Create an object which calculates quality via mean square error.
         /// </summary>
         /// <param name="refImgs">input image(s) to use as the source for comparison</param>
-        public QualitySSIM(IInputArray refImgs)
+        public QualitySSIM(IInputArrayOfArrays refImgs)
         {
             using (InputArray iaRefImgs = refImgs.GetInputArray())
                 _ptr = QualityInvoke.cveQualitySSIMCreate(

Emgu.CV.Contrib/Stereo/QuasiDenseStereo.cs

@@ -14,8 +14,16 @@
 
 namespace Emgu.CV.Stereo
 {
+    /// <summary>
+    /// Class containing the methods needed for Quasi Dense Stereo computation.
+    /// </summary>
     public partial class QuasiDenseStereo : SharedPtrObject
     {
+        /// <summary>
+        /// Create a new instance containing the methods needed for Quasi Dense Stereo computation.
+        /// </summary>
+        /// <param name="monoImgSize">Image size</param>
+        /// <param name="paramFilepath">The path for the parameters</param>
         public QuasiDenseStereo(Size monoImgSize, String paramFilepath = "")
         {
             using (CvString csParamFilePath = new CvString(paramFilepath))
@@ -37,18 +45,33 @@ protected override void DisposeObject()
             }
         }
 
+        /// <summary>
+        /// Main process of the algorithm. This method computes the sparse seeds and then densifies them.
+        /// Initially input images are converted to gray-scale and then the sparseMatching method is called to obtain the sparse stereo. Finally quasiDenseMatching is called to densify the corresponding points.
+        /// </summary>
+        /// <param name="imgLeft">The left Channel of a stereo image pair.</param>
+        /// <param name="imgRight">The right Channel of a stereo image pair.</param>
+        /// <remarks>If input images are in color, the method assumes that are BGR and converts them to grayscale.</remarks>
         public void Process(Mat imgLeft, Mat imgRight)
         {
             StereoInvoke.cveQuasiDenseStereoProcess(_ptr, imgLeft, imgRight);
         }
 
+        /// <summary>
+        /// Compute and return the disparity map based on the correspondences found in the "process" method.
+        /// </summary>
+        /// <param name="disparityLvls">The level of detail in output disparity image.</param>
+        /// <returns>Mat containing a the disparity image in grayscale.</returns>
         public Mat GetDisparity(byte disparityLvls = (byte)50)
         {
             Mat disparity = new Mat();
             StereoInvoke.cveQuasiDenseStereoGetDisparity(_ptr, disparityLvls, disparity);
             return disparity;
         }
 
+        /// <summary>
+        /// The propagation parameters
+        /// </summary>
         public struct PropagationParameters
         {
             /// <summary>