The visual system is highly sensitive to spatial context for encoding luminance patterns.
Context sensitivity inspired the proposal of many neural mechanisms for explaining the …

Lightness illusions are fundamental to human perception, and yet why we see them is still
the focus of much research. Here we address the question by modelling not human …

This chapter describes the Attentive Vision Filter (AVF) model, in which attention and
feedback play an important role in modelling brightness perception. This model has the …

We introduce two new low-level computational models of brightness perception that account
for a wide range of brightness illusions, including many variations on White's Effect …

The present work proposes a new architecture for brightness perception, which aims to unify
image processing with brightness perception. A successful unification has not been …

The human brain is renowned for its dynamic regulation of sensory inputs, which enables
our brain to operate under an enormous range of physical energy with sensory neurons …

Abstract Conventional Difference of Gaussian (DOG) filter is usually used to model the early
stage of visual processing. However, convolution operation used with DOG does not …

Artists and astronomers noticed centuries ago that humans perceive dark features in an
image differently from light ones; however, the neuronal mechanisms underlying these …

Last year at HVEI, I presented a computational model of lightness perception inspired by
data from primate neurophysiology. That model first encodes local spatially-directed local …

The same target luminance in different contexts can elicit markedly different perceptions of
brightness, a fact that has long puzzled vision scientists. Here we test the proposal that the …