洞見 - Video Technology - # Quality Assessment of HDR Videos

Subjective Quality Assessment of Compressed Tone-Mapped High Dynamic Range Videos

Q: How can we ensure accurate subjective quality assessments when viewing videos on different display devices

To ensure accurate subjective quality assessments when viewing videos on different display devices, several factors need to be considered. Display Calibration: Display calibration is crucial to ensure that the colors and brightness levels are accurately represented. By calibrating displays to industry standards, such as Rec. 709 or BT.2020 for SDR and HDR content respectively, viewers can experience the content as intended by the creators. Ambient Lighting Conditions: Viewing videos in varying lighting conditions can impact how the content appears on different displays. Controlling ambient lighting or using bias lighting behind the display can help create a consistent viewing environment. Resolution and Color Gamut Compatibility: Ensuring that the display device supports the resolution and color gamut of the video being viewed is essential for an accurate representation of visual quality. Viewing Distance: The distance at which viewers watch videos can affect their perception of quality. Maintaining an optimal viewing distance based on screen size and resolution can enhance accuracy in subjective assessments. Cross-Device Testing: Conducting subjective tests across multiple devices with varying specifications allows for a broader understanding of how content translates across different screens.

Q: What challenges might arise when adapting TMOs for scene-level tone-mapping across multiple frames

Adapting TMOs for scene-level tone-mapping across multiple frames presents several challenges: Consistency Across Frames: Ensuring consistency in tone-mapping parameters across frames within a scene is crucial to maintain temporal coherency and avoid jarring transitions between frames. Scene Change Detection: Detecting scene changes accurately is necessary to apply appropriate tone-mapping parameters specific to each scene without introducing artifacts at transition points. Computational Complexity: Scene-level tone-mapping may require additional computational resources due to processing requirements for analyzing entire scenes rather than individual frames. 4 .Parameter Estimation Accuracy: Precise estimation of key parameters at a scene level, such as luminance values or contrast ratios, is essential for effective tone mapping without introducing distortions.

Q: How can advancements in compression technology improve visual quality in streaming HDR content

Advancements in compression technology have significant potential to improve visual quality in streaming HDR content through various means: 1 .Efficient Encoding Algorithms: Advanced encoding algorithms like HEVC (H265) offer better compression efficiency compared to traditional codecs like H264, allowing higher-quality video streams at lower bitrates. 2 .Dynamic Range Compression: Techniques that intelligently compress dynamic range while preserving perceptual quality enable smoother gradients and reduced banding artifacts in HDR content during streaming. 3 .Adaptive Bitrate Streaming: Adaptive bitrate streaming dynamically adjusts video quality based on available bandwidth, ensuring optimal playback performance without sacrificing visual fidelity. 4 .Content-Aware Encoding: Content-aware encoding techniques analyze video characteristics to allocate bits more efficiently where they are most needed, enhancing overall visual quality while maintaining compression ratios. These advancements collectively contribute towards delivering high-quality HDR streaming experiences by optimizing compression efficiency and minimizing artifacts associated with data reduction during transmission over networks.

核心概念

HDR videos require tone-mapping for SDR displays, impacting visual quality.

摘要

The article discusses the impact of tone-mapping on the visual quality of streaming HDR videos. It introduces the LIVE-TMHDR database, containing 15,000 tone-mapped sequences from 40 unique HDR source contents. The study analyzes subjective perception and objective prediction of video qualities, comparing various tone-mapping operators. Different TMOs are explored, along with spatial parameters and temporal modes to vary distortions. The study also delves into lossy compression effects on video quality.

統計資料

"The videos in the database were labeled with more than 750,000 subjective quality annotations."
"The database contains 40 source HDR videos and 15,000 tone-mapped sequences."
"Two OETFs have been included in the BT.2100 standard: PQ and HLG."
"A key reason for limited streaming of HDR content is the scarcity of true HDR displays supporting at least 1000 nits."
"Eilertsen et al. applied eleven TMOs to six source HDR videos creating a database of 66 videos."

引述

"High Dynamic Range (HDR) videos are expected to grow into the dominant video modality of the future."
"We envision that the new LIVE Tone-Mapped HDR (LIVE-TMHDR) database will enable significant progress on HDR video tone mapping and quality assessment in the future."
"The rest of the paper is organized as follows: Section II provides background regarding subjective quality assessment..."

從以下內容提煉的關鍵洞見

Subjective Quality Assessment of Compressed Tone-Mapped High Dynamic Range Videos

by Abhinau K. V... 於 arxiv.org 03-25-2024

https://arxiv.org/pdf/2403.15061.pdf

Subjective Quality Assessment of Compressed Tone-Mapped High Dynamic Range Videos

深入探究

How can we ensure accurate subjective quality assessments when viewing videos on different display devices

To ensure accurate subjective quality assessments when viewing videos on different display devices, several factors need to be considered.

Display Calibration: Display calibration is crucial to ensure that the colors and brightness levels are accurately represented. By calibrating displays to industry standards, such as Rec. 709 or BT.2020 for SDR and HDR content respectively, viewers can experience the content as intended by the creators.

Ambient Lighting Conditions: Viewing videos in varying lighting conditions can impact how the content appears on different displays. Controlling ambient lighting or using bias lighting behind the display can help create a consistent viewing environment.

Resolution and Color Gamut Compatibility: Ensuring that the display device supports the resolution and color gamut of the video being viewed is essential for an accurate representation of visual quality.

Viewing Distance: The distance at which viewers watch videos can affect their perception of quality. Maintaining an optimal viewing distance based on screen size and resolution can enhance accuracy in subjective assessments.

Cross-Device Testing: Conducting subjective tests across multiple devices with varying specifications allows for a broader understanding of how content translates across different screens.

What challenges might arise when adapting TMOs for scene-level tone-mapping across multiple frames

Adapting TMOs for scene-level tone-mapping across multiple frames presents several challenges:

Consistency Across Frames: Ensuring consistency in tone-mapping parameters across frames within a scene is crucial to maintain temporal coherency and avoid jarring transitions between frames.

Scene Change Detection: Detecting scene changes accurately is necessary to apply appropriate tone-mapping parameters specific to each scene without introducing artifacts at transition points.

Computational Complexity: Scene-level tone-mapping may require additional computational resources due to processing requirements for analyzing entire scenes rather than individual frames.

4 .Parameter Estimation Accuracy: Precise estimation of key parameters at a scene level, such as luminance values or contrast ratios, is essential for effective tone mapping without introducing distortions.

How can advancements in compression technology improve visual quality in streaming HDR content

Advancements in compression technology have significant potential to improve visual quality in streaming HDR content through various means:
1 .Efficient Encoding Algorithms: Advanced encoding algorithms like HEVC (H265) offer better compression efficiency compared to traditional codecs like H264, allowing higher-quality video streams at lower bitrates.
2 .Dynamic Range Compression: Techniques that intelligently compress dynamic range while preserving perceptual quality enable smoother gradients and reduced banding artifacts in HDR content during streaming.
3 .Adaptive Bitrate Streaming: Adaptive bitrate streaming dynamically adjusts video quality based on available bandwidth, ensuring optimal playback performance without sacrificing visual fidelity.
4 .Content-Aware Encoding: Content-aware encoding techniques analyze video characteristics to allocate bits more efficiently where they are most needed, enhancing overall visual quality while maintaining compression ratios.
These advancements collectively contribute towards delivering high-quality HDR streaming experiences by optimizing compression efficiency and minimizing artifacts associated with data reduction during transmission over networks.

Subjective Quality Assessment of Compressed Tone-Mapped High Dynamic Range Videos