A bio-inspired image coder with temporal scalability

TL;DR

This paper introduces a bio-inspired image coding scheme modeled after the mammalian retina, utilizing its temporal behavior to achieve scalable and efficient image compression without artifacts.

Contribution

It presents a novel retina-inspired coding model that exploits temporal dynamics for scalable image compression, inspired by the Virtual Retina model.

Findings

Enables scalable image coding with temporal bit allocation.

Produces high-quality decoded images without ringing or block artifacts.

Demonstrates biologically plausible approach to image compression.

Abstract

We present a novel bio-inspired and dynamic coding scheme for static images. Our coder aims at reproducing the main steps of the visual stimulus processing in the mammalian retina taking into account its time behavior. The main novelty of this work is to show how to exploit the time behavior of the retina cells to ensure, in a simple way, scalability and bit allocation. To do so, our main source of inspiration will be the biologically plausible retina model called Virtual Retina. Following a similar structure, our model has two stages. The first stage is an image transform which is performed by the outer layers in the retina. Here it is modelled by filtering the image with a bank of difference of Gaussians with time-delays. The second stage is a time-dependent analog-to-digital conversion which is performed by the inner layers in the retina. Thanks to its conception, our coder enables scalability and bit allocation across time. Also, our decoded images do not show annoying artefacts such as ringing and block effects. As a whole, this article shows how to capture the main properties of a biological system, here the retina, in order to design a new efficient coder.