Towards a Biologically Plausible Stereo Approach

A computational model for stereoscopic disparity estimation has been recently introduced which reformulates, in neurophysiologically plausible terms, the traditional image matching approach (Torreão, 2007). The left and right stereo images are assumed viewed through the receptive fields of cortical simple cells, modeled as Gabor functions (Marcelja, 1980). The Green’s functions of a matching equation (whose uniform solutions are also Gabor functions) are used to filter the receptive-field modulated inputs, introducing different relative shifts between them. A measure of the local degree of matching of such shifted inputs can then be used for the estimation of stereoscopic disparities, in a way which is reminiscent of the energy model for the responses of cortical complex cells (Adelson & Bergen, 1985; Ohzawa et al., 1997). Although based on well-established neurophysiological concepts, the Green’s function approach is still far from being biologically plausible. For instance, it assumes as cortical inputs the original irradiance images, disregarding the transformations performed by the earlier stages of the visual pathway− namely, the retina and the lateral geniculate nucleus. As a further step towards a fully biological stereo, we here introduce an improved version of the algorithm in (Torreão, 2007), incorporating a new concept of signal coding by input-dependent receptive fields (Torreão et al., 2009). The classical receptive field description, which assumes a fixed, stimulus-independent spatial organization, has recently been challenged by neurophysiological indications that the receptive-field structure does change with neuronal input (Allman et al., 1985; Bair, 2005; David et al., 2004). In (Torreão et al., 2009), a signal coding scheme has been introduced, where the parameters of the coding functions are obtained from the Fourier transform of the coded signal, and, in (Torreão & Victer, 2010), such scheme has been taken up as a model for stimulus-dependent center-surround (CS) receptive fields, such as those found in the retina and in the lateral geniculate nucleus. Assuming that the role of the CS structures is that of decorrelating natural images, as suggested in (Attick & Redlich, 1992) and (Dan et al., 1996), center-surround receptive fields which code whitened versions of the input signals have been obtained. We show that, by incorporating a similar center-surround coding module into the Green’s function stereo algorithm, we are able to obtain better quality disparity estimates, through an approach which is closer to the neurophysiological situation. Towards a Biologically Plausible Stereo Approach