Abstract
The human visual system is composed of multiple physiological components that apply multiple mechanisms in order to cope with the rich visual content it encounters. The complexity of this system leads to non-trivial relations between what we see and what we perceive, and in particular, between the raw intensities of an image that we display and the ones we perceive where various visual biases and illusions are introduced. In this paper, we describe a method for reducing a large class of biases related to the lateral inhibition mechanism in the human retina where neurons suppress the activity of neighbouring receptors. Among these biases are the well-known Mach bands and halos that appear around smooth and sharp image gradients as well as the appearance of false contrasts between identical regions. The new method removes these visual biases by computing an image that contains counter biases such that when this laterally compensated image is viewed on a display, the inserted biases cancel the ones created in the retina. User study results confirm the usefulness of the new approach for displaying various classes of images, visualizing physical data more faithfully and improving the ability to perceive constancy in brightness.
The human visual system is composed of multiple physiological components that apply multiple mechanisms in order to cope with the rich visual content it encounters. The complexity of this system leads to non-trivial relations between what we see and what we perceive, and in particular, between the raw intensities of an image that we display and the ones we perceive where various visual biases and illusions are introduced. In this paper, we describe a method for reducing a large class of biases related to the lateral inhibition mechanism in the human retina where neurons suppress the activity of neighbouring receptors.