Mechanisms for similarity matching in disparity measurement.
Early neural mechanisms for the measurement of binocular disparity appear to operate in a manner consistent with cross-correlation-like processes. Consequently, cross-correlation, or cross-correlation-like procedures have been used in a range of models of disparity measurement. Using such procedures as the basis for disparity measurement creates a preference for correspondence solutions that maximize the similarity between local left and right eye image regions. Here, we examine how observers' perception of depth in an ambiguous stereogram is affected by manipulations of luminance and orientation-based image similarity. Results show a strong effect of coarse-scale luminance similarity manipulations, but a relatively weak effect of finer-scale manipulations of orientation similarity. This is in contrast to the measurements of depth obtained from a standard cross-correlation model. This model shows strong effects of orientation similarity manipulations and weaker effects of luminance similarity. In order to account for these discrepancies, the standard cross-correlation approach may be modified to include an initial spatial frequency filtering stage. The performance of this adjusted model most closely matches human psychophysical data when spatial frequency filtering favors coarser scales. This is consistent with the operation of disparity measurement processes where spatial frequency and disparity tuning are correlated, or where disparity measurement operates in a coarse-to-fine manner.
['Goutcher|Ross|R|', 'Hibbard|Paul B|PB|']
similarity disparity measurement cross-correlation binocular energy model binocular vision correspondence problem