In this paper, we introduce some new notions of perception and cognitive vision fields for the emulation of human vision. The attributes of an image (edges, colors, etc.) are assumed to have graded membership values distributed over the interval [0,1]. These graded attributes are responsible for the formation of cognitive fields. The information contained in these cognitive vision fields are extracted using numerous densely packed units called percepts. The "percept" is a neuron-like computational unit that responds to a group of neighborhood pixels rather than individual image pixels. Examples of cognitive vision fields for two gray-level images are presented.