This paper presents an original algorithm called the ``Orthogonal Algorithm'' for image matching using dynamic programming and experimental results from its application to stereovision and image interpolation.
The algorithm provides a dense, continuous and differentiable field of bidimensional displacements like classical optical flow detection algorithms. It is based on an iterative search for a displacement field that minimizes the L1 or L2 distance between two images. Both images are sliced into parallel and overlapping strips. Corresponding strips are aligned using dynamic programming exactly as 2D representations of speech signal are with the DTW algorithm. Two passes are performed using orthogonal slicing directions. This process is iterated in a pyramidal fashion while reducing the spacing and width of the strips. Very good results have been obtained for stereovision and image interpolation.