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

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.