Neuronal Mechanism for Compensation of Longitudinal Chromatic Aberration-Derived Algorithm.

Yuval Barkan,Hedva Spitzer

doi:10.3389/fbioe.2018.00012

Yuval Barkan, Hedva Spitzer

Open Access

https://doi.org/10.3389/fbioe.2018.00012

Copy DOI

Abstract

The human visual system faces many challenges, among them the need to overcome the imperfections of its optics, which degrade the retinal image. One of the most dominant limitations is longitudinal chromatic aberration (LCA), which causes short wavelengths (blue light) to be focused in front of the retina with consequent blurring of the retinal chromatic image. The perceived visual appearance, however, does not display such chromatic distortions. The intriguing question, therefore, is how the perceived visual appearance of a sharp and clear chromatic image is achieved despite the imperfections of the ocular optics. To address this issue, we propose a neural mechanism and computational model, based on the unique properties of the S-cone pathway. The model suggests that the visual system overcomes LCA through two known properties of the S channel: (1) omitting the contribution of the S channel from the high-spatial resolution pathway (utilizing only the L and M channels). (b) Having large and coextensive receptive fields that correspond to the small bistratified cells. Here, we use computational simulations of our model on real images to show how integrating these two basic principles can provide a significant compensation for LCA. Further support for the proposed neuronal mechanism is given by the ability of the model to predict an enigmatic visual phenomenon of large color shifts as part of the assimilation effect.

Highlights

The human eye is affected by the imperfections of its optics, which degrade the quality of the retinal image and impose limits on vision
The model significantly reduces the distortion caused by longitudinal chromatic aberration (LCA), it can cause some minor chromatic artifacts
The predicted chromatic shifts, between the two test chromaticities in terms of chromatic contrast [S/(L + M)], are about 0.31. This shift agrees with the perceived colors as measured psychophysically by Shevell and Monnier. This manuscript describes a neuronal mechanism and a computational model, based on retinal chromatic receptive fields (RFs) and visual pathways, that compensate for LCA

Summary

INTRODUCTION

The human eye is affected by the imperfections of its optics, which degrade the quality of the retinal image and impose limits on vision. This adaptation of the visual system supports the existence of a long-term corrective neural compensation mechanism These models can be accounted for neuronal compensation only when the chromatic aberration refractive power is constant. The model computes the perceived color in accordance with the response of retinal color-coding ganglion cells (Daw, 2012) The “center” signals of the two spectral regions, Lcen, Mcen, are defined as integrals of the adapted inputs (Ladapted, Madapted; Eq 1) over the center subregion, with a Gaussian decaying spatial weight function (fc): ∫∫. The spatial weight function of the RF, fc_center, is defined as in Eq 7 The purpose of this stage is to model how the visual system transforms the RF responses to a perceived image. The perceived brightness is expressed solely by the L and M values

METHODS

RESULT

Findings

DISCUSSION