From primal sketches to the recovery of intensity and reflectance representations

Abstract

A local change in intensity (edge) is a characteristic that is preserved when an image is filtered through a bandpass filter. Primal sketch representations of images, using the bandpass-filtered data, have become a common process since Marr proposed his model for early human vision. Here, researchers move beyond the primal sketch extraction to the recovery of intensity and reflectance representations using only the bandpass-filtered data. Assessing the response of an ideal step edge to the Laplacian of Gaussian (NAb/A squared G) filter, they found that the resulting filtered data preserves the original change of intensity that created the edge in addition to the edge location. Using the filtered data, they can construct the primal sketches and recover the original (relative) intensity levels between the boundaries. It was found that the result of filtering an ideal step edge with the Intensity-Dependent Spatial Summation (IDS) filter preserves the actual intensity on both sides of the edge, in addition to the edge location. The IDS filter also preserves the reflectance ratio at the edge location. Therefore, one can recover the intensity levels between the edge boundaries as well as the (relative) reflectance representation. The recovery of the reflectance representation is of special interest as it erases shadowing degradations and other dependencies on temporal illumination. This method offers a new approach to low-level vision processing as well as to high data-compression coding. High compression can be gained by transmitting only the information associated with the edge location (edge primitives) that is necessary for the recover