A Mathematical Model of Retinal Ganglion Cells and Its Applications in Image Representation

摘要

Contrast stimuli are the essential components that constitute visual scenes. This paper studies how retinal ganglion cells respond to a contrast stimulus covering their concentric receptive fields with center-surround antagonism, and thereby proposes a mathematical model that describes the response by the multiplication of the contrast of the stimulus and a normalized response function with respect to the coverage ratio and the center/surround ratio. The obtained response curves turn out to be consistent with physiological data. This model partially accounts for the contrast sensitivities of ganglion cells and the invariance of visual perception to the contrast. A computational approach based on this neural model is developed for orientation detection, and is further applied to image representation. The experiments achieve convincing results on challenging image datasets. Moreover, it is revealed that the produced orientation maps remarkably enhance the efficiencies and the effectiveness of segmentation algorithms.