Measuring Perceptual Color Differences of Smartphone Photographs

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

View graph of relations

Author(s)

  • Keshuo Xu
  • Yang Yang
  • Jianlei Dong
  • Shuhang Gu
  • Lihao Xu
  • Yuming Fang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)10114-10128
Number of pages15
Journal / PublicationIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume45
Issue number8
Online published28 Mar 2023
Publication statusPublished - Aug 2023

Abstract

Measuring perceptual color differences (CDs) is of great importance in modern smartphone photography. Despite the long history, most CD measures have been constrained by psychophysical data of homogeneous color patches or a limited number of simplistic natural photographic images. It is thus questionable whether existing CD measures generalize in the age of smartphone photography characterized by greater content complexities and learning-based image signal processors. In this paper, we put together so far the largest image dataset for perceptual CD assessment, in which the photographic images are 1) captured by six flagship smartphones, 2) altered by Photoshop®, 3) post-processed by built-in filters of the smartphones, and 4) reproduced with incorrect color profiles. We then conduct a large-scale psychophysical experiment to gather perceptual CDs of 30,000 image pairs in a carefully controlled laboratory environment. Based on the newly established dataset, we make one of the first attempts to construct an end-to-end learnable CD formula based on a lightweight neural network, as a generalization of several previous metrics. Extensive experiments demonstrate that the optimized formula outperforms 33 existing CD measures by a large margin, offers reasonable local CD maps without the use of dense supervision, generalizes well to homogeneous color patch data, and empirically behaves as a proper metric in the mathematical sense. Our dataset and code are publicly available at https://github.com/hellooks/CDNet. © 2023 IEEE.

Research Area(s)

  • Color, Color difference, color perception, Colored noise, Image color analysis, image signal processing, Lighting, Measurement, Photography, smartphone photography, Visualization

Citation Format(s)

Measuring Perceptual Color Differences of Smartphone Photographs. / Wang, Zhihua; Xu, Keshuo; Yang, Yang et al.
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 45, No. 8, 08.2023, p. 10114-10128.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review