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Compressed-SDR to HDR Video Reconstruction.

Hu Wang, Mao Ye, Xiatian Zhu

IEEE Transactions on Pattern Analysis and Machine Intelligence

|December 25, 2023

Summary

This study introduces KPNet, a novel method for converting compressed standard dynamic range (SDR) videos to high dynamic range (HDR) format. KPNet effectively addresses video compression artifacts and enhances visual quality for modern displays.

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Area of Science:

Computer Vision
Image Processing
Display Technology

Background:

New organic light-emitting diode displays support high dynamic range (HDR), surpassing traditional standard dynamic range (SDR) capabilities.
A significant volume of existing video content is in SDR format and often compressed, posing challenges for playback on HDR devices.

Purpose of the Study:

To develop an effective method for converting compressed SDR videos to HDR format (CSDR-to-HDR conversion).
To address the inherent many-to-many mapping challenge in SDR-to-HDR conversion, particularly for compressed videos.

Main Methods:

Proposed a novel imaging knowledge-inspired parallel network (KPNet) for CSDR-to-HDR video reconstruction.
KPNet utilizes Knowledge-Inspired Blocks (KIBs) and an Information Fusion Module (IFM).
The process involves reducing compression artifacts, recovering details, adjusting imaging parameters, and reducing noise, approximated by KIBs.

Main Results:

KPNet demonstrated superior performance compared to existing state-of-the-art methods in CSDR-to-HDR video reconstruction.
The parallel network architecture with KIBs and IFM effectively captures richer HDR details.
The method explicitly formulates the HDR video generation process, overcoming limitations of prior approaches.

Conclusions:

KPNet offers a robust solution for CSDR-to-HDR video conversion, enhancing visual experiences on HDR displays.
The proposed architecture effectively handles video compression and improves the quality of reconstructed HDR content.
This work advances the field of video format conversion for next-generation display technologies.