Perceptually motivated model for predicting banding artefacts in high-dynamic range images

Minjung Kim,Rafał K Mantiuk,Maryam Azimi

doi:10.2352/issn.2169-2629.2020.28.8

Abstract

Banding is a type of quantisation artefact that appears when a low-texture region of an image is coded with insufficient bitdepth. Banding artefacts are well-studied for standard dynamic range (SDR), but are not well-understood for high dynamic range (HDR). To address this issue, we conducted a psychophysical experiment to characterise how well human observers see banding artefacts across a wide range of luminances (0.1 cd/m2–10,000 cd/m2). The stimuli were gradients modulated along three colour directions: black-white, red-green, and yellow-violet. The visibility threshold for banding artefacts was the highest at 0.1 cd/m2, decreased with increasing luminance up to 100 cd/m2, then remained at the same level up to 10,000 cd/m2. We used the results to develop and validate a model of banding artefact detection. The model relies on the contrast sensitivity function (CSF) of the visual system, and hence, predicts the visibility of banding artefacts in a perceptually accurate way.

Highlights

Representing colour requires the conversion of continuous values into discrete ones
Our model operates on physical units of luminance and contrast, rather than relative pixel values, and is deviceand content-independent
The detection threshold was the lowest for redgreen, followed by achromatic, and the highest for yellow-violet. This is consistent with what we know about the contrast sensitivity function (CSF): red-green contrast sensitivity is much higher than the achromatic, which is in turn more sensitive than yellow-violet

Summary

Introduction

Representing colour requires the conversion of continuous values into discrete ones. If an insufficient number of bits are used to represent the digital value, human observers may see edges in the quantised image (Fig. 1), called banding or contouring artefacts. There is a trade-off: minimising the appearance of banding artefacts requires encoding with higher bit-depth, but higher bit-depth necessarily results in more data. This is undesirable, as there is an immense amount of visual content that is created, stored, and streamed daily; high-definition streaming is only possible with lossy video coding [2]. On the other hand, encoding with insufficient bit-depth results in unattractive banding, and for some applications, such as medical imaging, illusory bands may even result in incorrect diagnosis [3]

Methods

Results

Conclusion