Color Pass-Through via Camera-Display Coupling

2026-07-14 · Source: Computer Vision and Pattern Recognition · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Computer Vision · Depth: Expert, quick

Summary

Color Pass-Through is an end-to-end learned framework designed to resolve the persistent color, brightness, and contrast discrepancies between real-world scenes captured by smartphone cameras and their display on screen. This issue typically arises from traditional pipelines that calibrate camera and display stages separately, using low-dimensional color transforms that create information bottlenecks and accumulate errors. The proposed framework addresses this by treating the camera and display as a single, coupled system, enabling end-to-end optimization to bring entire real-world scenes to the display. This approach also facilitates efficient one-step calibration tailored for each distinct observer. Validated with both digital and human observers, Color Pass-Through achieved an average gain of +2.0 points on a 5-point user study and demonstrated over 2x improvement on quantitative metrics, significantly enhancing the perceived color reproduction of original scenes compared to representative baselines.

Key takeaway

For computer vision engineers developing smartphone imaging pipelines, recognize that traditional separate camera and display calibration methods create inherent color reproduction bottlenecks. You should explore end-to-end learned frameworks like Color Pass-Through, which treat the camera and display as a coupled system. This approach offers over 2x quantitative improvement and simplifies user-specific calibration, significantly enhancing your device's perceived color accuracy for users.

Key insights

Coupling smartphone cameras and displays as a single system improves perceived color reproduction by overcoming traditional calibration bottlenecks.

Principles

• Calibrate camera and display as a coupled system.
• Optimize the entire capture-to-display path end-to-end.
• Enable efficient one-step calibration per observer.

Method

An end-to-end learned framework processes captured images, optimizing the entire camera-display path as a unified system.

In practice

• Enhance smartphone display color accuracy.
• Streamline user-specific display calibration.

Topics

• Color Pass-Through
• Camera-Display Coupling
• End-to-End Learning
• Smartphone Imaging
• Color Reproduction
• Display Calibration

Best for: Research Scientist, AI Scientist, Computer Vision Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Computer Vision and Pattern Recognition.