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Measuring Spatially- and Directionally-varying Light Scattering from Biological Material

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Multi-Frame Content-Aware Mapping Network for Standard-Dynamic-Range to High-Dynamic-Range Television Artifact

Zheng Wang¹, Gang He¹

¹School of Telecommunications Engineering, Xidian University, Xi'an 710071, China.

Sensors (Basel, Switzerland)

|January 11, 2024

Summary

This study introduces a multi-frame content-aware mapping network (MCMN) to convert standard-dynamic-range television (SDRTV) to high-dynamic-range television (HDRTV). The MCMN effectively enhances visual quality by addressing video encoding artifacts during SDRTV to HDRTV conversion.

Keywords:

artifact removal high dynamic range (HDR)standard dynamic range (SDR)video coding

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Area of Science:

Computer Vision
Image Processing
Video Technology

Background:

Advancements in high-dynamic-range television (HDRTV) technology have increased demand for converting standard-dynamic-range television (SDRTV) content.
A significant challenge in SDRTV to HDRTV conversion is the amplification of existing video encoding artifacts, degrading output quality.

Purpose of the Study:

To propose a novel multi-frame content-aware mapping network (MCMN) for high-quality SDRTV to HDRTV conversion.
To mitigate the amplification of video encoding artifacts during the conversion process.

Main Methods:

Development of a content-aware temporal spatial alignment module to leverage video's temporal and spatial characteristics.
Introduction of a hybrid prior extraction module incorporating cross-temporal, local spatial, and global spatial priors.
Design of a temporal spatial transformation module for improved tone mapping and artifact repair.

Main Results:

The MCMN effectively utilizes multi-frame information for single-frame inverse tone mapping.
The proposed method demonstrates improved performance in converting low-quality SDRTV to high-quality HDRTV.
Significant reduction in amplified video encoding artifacts was observed.

Conclusions:

The MCMN offers a robust solution for SDRTV to HDRTV conversion, enhancing visual fidelity.
The network's ability to leverage multi-frame data and repair artifacts makes it suitable for real-world applications.
This approach addresses a critical limitation in current video conversion techniques.