pandora.aggregation.cpp.aggregation_cpp
=======================================

.. py:module:: pandora.aggregation.cpp.aggregation_cpp


Functions
---------

.. autoapisummary::

   pandora.aggregation.cpp.aggregation_cpp.cbca
   pandora.aggregation.cpp.aggregation_cpp.cross_support


Module Contents
---------------

.. py:function:: cbca(input, cross_left, cross_right, range_col, range_col_right)

   Build the fully aggregated matching cost for one disparity,
   E = S_v(row, col + bottom_arm_length) - S_v(row, col - top_arm_length - 1)

   :param input: cost volume for the current disparity
   :type input: 2D np.array (row, col) dtype = np.float32
   :param cross_left: cross support of the left image
   :type cross_left: 3D np.array (row, col, [left, right, top, bot]) dtype=np.int16
   :param cross_right: cross support of the right image
   :type cross_right: 3D np.array (row, col, [left, right, tpo, bot]) dtype=np.int16
   :param range_col: left column for the current disparity (i.e : np.arrange(nb columns), where the correspondent     in the right image is reachable)
   :type range_col: 1D np.array
   :param range_col_right: right column for the current disparity (i.e : np.arrange(nb columns) - disparity, where     column - disparity >= 0 and <= nb columns)
   :type range_col_right: 1D np.array
   :return: the fully aggregated matching cost, and the total number of support pixels used for the aggregation
   :rtype: tuple(2D np.array (row , col) dtype = np.float32, 2D np.array (row , col) dtype = np.float32)


.. py:function:: cross_support(image, len_arms, intensity)

   Compute the cross support for an image: find the 4 arms.
   Enforces a minimum support region of 3×3 if pixels are valid.
   The cross support of invalid pixels (pixels that are np.inf) is 0 for the 4 arms.

   :param image: image
   :type image: 2D np.array (row , col) dtype = np.float32
   :param len_arms: maximal length arms
   :param len_arms: int16
   :param intensity: maximal intensity
   :param intensity: float 32
   :return: a 3D np.array ( row, col, [left, right, top, bot] ), with the four arms lengths computes for each pixel
   :rtype:  3D np.array ( row, col, [left, right, top, bot] ), dtype=np.int16