Analog computation for phase-based disparity
estimation: Continuous and discrete models.

Bruno Crespi
IRST-ITC, 38050 Povo, Trento, ITALY
Alex G. Cozzi
Dept. of Neurophysiology - Ruhr University, Bochum, GERMANY
Luigi Raffo
DIEE - University of Cagliari, Piazza d'Armi, 09123 Cagliari, ITALY
Silvio P. Sabatini
DIBE - University of Genoa, Via Opera Pia 11a, 16145 Genova, ITALY

The analog implementation of a phase-based technique for disparity
estimation is discussed. This technique is based on the convolution of
images with Gabor filters. The article shows that by replacing the Gaussian
envelope with other envelopes, the convolution operation is equivalent to
the solution of a system of differential equations, whose order is related
to the smoothness of the kernel. A detailed comparison between the
disparity estimates obtained using these kernels and those obtained using
the standard filter is presented. The discretization of the model leads to
lattice networks in which the number of connections per node required to
perform convolution is limited to the first few nearest neighbors. The
short connection length makes these filter suitable for analog VLSI
implementation, for which the number of connection per node is a crucial
factor. Experimental measures on a prototype CMOS 17-node chip validated
the approach.