Cost Aggregation

Theoretical basics

The second step is to aggregate the matching costs:

• Cross-based Cost Aggregation [Zhang2009]. This method consists in creating aggregation support regions that adapt to the structures present in the scene, it is performed in 5 steps:

  • a 3x3 median filter is applied to the left image (left image) and the right image (right image),

  • cross support region computation of each pixel of the left image,

  • cross support region computation of each pixel of the right image,

  • combination of the left and right support region,

  • the matching cost is averaged over the combined support region.

[Zhang2009]

Zhang, K., Lu, J., & Lafruit, G. (2009). Cross-based local stereo matching using orthogonal integral images. IEEE transactions on circuits and systems for video technology, 19(7), 1073-1079.

Configuration and parameters

Name	Description	Type	Default value	Available value	Required
aggregation_method	Aggregation method	string		“cbca”	Yes
cbca_intensity	Maximum intensity difference between 2 points	float	30.0	>0	No. Only available if “cbca” method
cbca_distance	Maximum distance difference between 2 points	int	5	>0	No. Only available if “cbca” method

Example

{
    "input" :
    {
        // ...
    },
    "pipeline" :
    {
        // ...
        "aggregation":
        {
            "aggregation_method": "cbca",
            "cbca_intensity": 25.0
        }
        // ...
    }
}