Stereo reconstruction is a process of estimating distance from a camera using a pair of 2D images. Two images can be taken that are a known, small, distance apart (i.e., a few centimeters) by using a pair of camera sensors. Video analysis can be implemented to detect various objects in images. By quantifying the small differences in position of various objects between the 2 images the distance of various objects can be estimated. Objects that have a smaller change in position between the two images are determined to be far away. Objects that have larger changes in position between the two images are closer to the camera.
Efficiently performing stereo reconstruction is of great utility when implementing computer vision. One implementation of stereo reconstruction involves computing costs along multiple 1-D paths towards each pixel. Processing an image in order takes advantage of a recurrence relation that defines each cost. However, one cost will be calculated along a path opposite to the order the pixels are presented. A memory buffer can be used to store pixels to calculate the path opposite to the order the pixels are presented.
In hardware implementation, it is important to find solutions that use as little hardware as possible, without loss in performance and output rate. One solution may implement a two line memory buffer where the data is written to one line while data is read out on the other line. A two line memory buffer solution has a larger memory hardware requirement.
It would be desirable to implement an efficient scheme for reversing image data in a memory buffer.