A Retina Inspired Model for Enhancing Visibility of Hazy Images.

Yong-Jie Li,Xian-Shi Zhang,Chao-Yi Li,Shao-Bing Gao

doi:10.3389/fncom.2015.00151

Abstract

The mammalian retina seems far smarter than scientists have believed so far. Inspired by the visual processing mechanisms in the retina, from the layer of photoreceptors to the layer of retinal ganglion cells (RGCs), we propose a computational model for haze removal from a single input image, which is an important issue in the field of image enhancement. In particular, the bipolar cells serve to roughly remove the low-frequency of haze, and the amacrine cells modulate the output of cone bipolar cells to compensate the loss of details by increasing the image contrast. Then the RGCs with disinhibitory receptive field surround refine the local haze removal as well as the image detail enhancement. Results on a variety of real-world and synthetic hazy images show that the proposed model yields results comparative to or even better than the state-of-the-art methods, having the advantage of simultaneous dehazing and enhancing of single hazy image with simple and straightforward implementation.

Highlights

The necessary processing of visual information already begins in the eye, the very first stage of the visual system
The receptive field (RF) of most bipolar cells consists of two regions: a smaller excitatory center and a lager inhibitory annular surround (Werblin and Dowling, 1969a; Kaneko and Tachibana, 1983), which is commonly described by the “difference of Gaussian” (DOG) model (Rodieck and Stone, 1965; Enroth-Cugell and Robson, 1966)
We first show the responsive properties of the model ganglion cells and the model bipolar cells involved in the proposed system to demonstrate how they contribute to the haze removal

Summary

A Retina Inspired Model for Enhancing Visibility of Hazy Images

Inspired by the visual processing mechanisms in the retina, from the layer of photoreceptors to the layer of retinal ganglion cells (RGCs), we propose a computational model for haze removal from a single input image, which is an important issue in the field of image enhancement. The bipolar cells serve to roughly remove the low-frequency of haze, and the amacrine cells modulate the output of cone bipolar cells to compensate the loss of details by increasing the image contrast. The RGCs with disinhibitory receptive field surround refine the local haze removal as well as the image detail enhancement. Results on a variety of real-world and synthetic hazy images show that the proposed model yields results comparative to or even better than the state-of-the-art methods, having the advantage of simultaneous dehazing and enhancing of single hazy image with simple and straightforward implementation.

INTRODUCTION

A Retina Inspired Model for Dehazing

EXPERIMENTS

Findings

DISCUSSION