Adaptive HDR/WCG Video Coding to Reduce Quantization Distortion
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Solution Overview
Problem
Existing video encoding and decoding schemes struggle to effectively handle High Dynamic Range (HDR) and Wide Color Gamut (WCG) video data, leading to quantization distortion and loss of detail due to fixed coding transfer functions that do not account for the content characteristics of the video.
Innovation Solution
Adaptive pre-processing and post-processing methods are applied to HDR and WCG video data, using color space conversions and perceptual transfer functions to optimize quantization, with metadata transmission for inverse operations at the decoder side, allowing efficient encoding and decoding while minimizing distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed coding transfer function is used to convert HDR input values to non-linear values, then the conversion process is simple and fast, but quantization distortion increases and detail is lost because the fixed mapping does not adapt to content characteristics
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed coding transfer function to an adaptive one that changes based on content characteristics. The system dynamically selects different transfer functions or parameters depending on the statistical properties of the input video data, allowing the quantization process to adapt to the actual content and maintain precision without sacrificing encoding speed.
Solution Approach 2:
The patent changes the parameters of the coding transfer function based on content characteristics. By analyzing the input data and adjusting transfer function parameters (such as gamma values, mapping curves, or quantization step sizes) to match the content's luminance and color distribution, the system achieves better quantization precision while maintaining efficient encoding.
2Stability of the object's composition
If a fixed coding transfer function maps all possible HDR values to non-linear values, then the mapping is consistent and simple, but similar shades in limited ranges (e.g., blue sky) are quantized into the same value causing contouring and banding
Solution Approach 1:
The patent applies local quality by making the transfer function adaptive to different regions and content characteristics rather than applying a uniform fixed mapping. The system analyzes content characteristics and adjusts the transfer function to provide appropriate quantization levels for different luminance and color ranges, ensuring that similar shades in limited ranges are differentiated with sufficient precision to avoid contouring and banding.
Solution Approach 2:
The system changes transfer function parameters based on the detected content characteristics. When analyzing the input video, the system adjusts mapping parameters to match the actual range and distribution of values present, preventing uniform quantization of similar shades and preserving color detail while maintaining mapping consistency for the given content.
3Device complexity
If HDR video data is directly encoded using existing SDR compression algorithms, then device complexity is reduced, but the algorithms cannot properly handle the broader luminance and color ranges leading to poor compression efficiency
Solution Approach 1:
The patent uses an intermediary approach by introducing an adaptive coding transfer function as a mediator between HDR input data and SDR compression algorithms. This transfer function converts HDR values to non-linear values in a way that is optimized for the compression algorithm's expectations, allowing existing SDR algorithms to handle HDR content efficiently without requiring fundamental changes to the compression architecture.
Solution Approach 2:
The system changes the parameter representation of HDR data through adaptive transfer functions to make it compatible with existing SDR compression algorithms. By transforming the data according to content characteristics, the system maintains compression efficiency while avoiding the need for complex HDR-specific algorithms, thus balancing device complexity with productivity.
Data Source
AI summary
A method of encoding a digital video data applies adaptive pre-processing to data representing high dynamic range (HDR) and/or wide color gamut (WCG) image data prior to encoding and complementary post-processing to the data after decoding in order to allow at least partial reproduction of the HDR and/or WCG data. The example methods apply one or more color space conversions, and a perceptual transfer functions to the data prior to quantization. The example methods apply inverse perceptual transfer functions and inverse color space conversions after decoding to recover the HDR and/or WCG data. The transfer functions are adaptive so that different transfer functions may be applied to video data sets including different groups of frames, frames or processing windows in a single frame. Information on the data set and information on the applied transfer function is passed as metadata from the encoder to the decoder.