A Generic Model to Improve Color Reproduction Accuracy of Mobile Displays: A Case Study on Apple Devices

Color visualization on websites and in apps usually tacitly assumes device-independent sRGB color space, bypassing the essential step of characterization—a process that requires expensive equipment and significant time. This work proposes a pseudo-device-independent approach applicable to Apple displays, one of the most renowned brands in this area, eliminating the need for characterization by leveraging the Mobile Display Characterization and Illumination Model (MDCIM). For this purpose, 11 Apple mobile displays were characterized, analyzing variations in parameters from spectroradiometer measurements and improving their sRGB tone rendering curves. Tested on an iPhone XS Max, the Color for the Average Apple Display model (CAAD) improved reasonable to good color matches from 4.0% to 84.3%, while incorrect matches dropped from 85.3% to 4.9% when compared to sRGB. These results are nearly as strong as those of the device-specific MDCIM, suggesting that an average model is a practical alternative to individual display characterization.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2025-06-19
DOI
https://doi.org/10.3390/app15126915
Citations
1
Primary Topic
Color Science and Applications
Type
article
Field-Weighted Citation Impact
1.25

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Generic Model to Improve Color Reproduction Accuracy of Mobile Displays: A Case Study on Apple Devices

Eric Kirchner, Esther Perales, Lan Njo, Julián Espinosa et al.
1 citations
Applied Sciences
Color Science and Applications
1.25
article

A Generic Model to Improve Color Reproduction Accuracy of Mobile Displays: A Case Study on Apple Devices

Eric Kirchner, Esther Perales, Lan Njo, Julián Espinosa, Carmen Vázquez, A. Larrosa
article en
1 citations

Abstract

Color visualization on websites and in apps usually tacitly assumes device-independent sRGB color space, bypassing the essential step of characterization—a process that requires expensive equipment and significant time. This work proposes a pseudo-device-independent approach applicable to Apple displays, one of the most renowned brands in this area, eliminating the need for characterization by leveraging the Mobile Display Characterization and Illumination Model (MDCIM). For this purpose, 11 Apple mobile displays were characterized, analyzing variations in parameters from spectroradiometer measurements and improving their sRGB tone rendering curves. Tested on an iPhone XS Max, the Color for the Average Apple Display model (CAAD) improved reasonable to good color matches from 4.0% to 84.3%, while incorrect matches dropped from 85.3% to 4.9% when compared to sRGB. These results are nearly as strong as those of the device-specific MDCIM, suggesting that an average model is a practical alternative to individual display characterization.

Applied SciencesVol. 15(12)
University of Alicante (ES), AkzoNobel (Netherlands) (NL)
Universidad de Alicante
Openalex Percentile: Top 20%
Color Science and Applications
1.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.