Adaptive Multi-Exposure Video Capture for High Dynamic Range Encoding
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Solution Overview
Problem
Current video capture and encoding technologies are limited in handling high dynamic range video data, leading to reduced quality due to encoder limitations and network bandwidth constraints, which restrict the effective transmission and display of HDR content.
Innovation Solution
The method involves capturing high dynamic range video data using multiple groups of pixels at different exposure times, which are then combined using interpolation to achieve a higher dynamic range, allowing for adaptive grouping based on image content and system resources, and transitioning between capture modes gradually to maintain video quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If video content is limited to 8-10 bit signal representations to keep complexity and cost low, then device complexity is reduced, but video quality and dynamic range are degraded
Solution Approach 1:
The image is divided into multiple regions with different exposure characteristics. Each region is processed independently with appropriate exposure time selection, allowing the system to handle high dynamic range content while maintaining compatibility with standard encoders. This segmentation enables quality improvement in critical regions without uniformly increasing complexity across the entire system.
Solution Approach 2:
Different regions of the image are assigned different quality levels based on their importance and exposure characteristics. Critical regions such as facial areas receive higher quality processing with longer exposure times, while less important regions use shorter exposure times. This local quality approach improves overall video quality without requiring uniform high complexity across all regions.
2Device complexity
If encoder bit depth is limited to handle high dynamic range video data, then device complexity is reduced, but dynamic range capture capability is degraded
Solution Approach 1:
Instead of increasing bit depth in the traditional dimension, the system adds a temporal dimension by capturing multiple frames with different exposure times. This allows the encoder to work with standard bit depths while the combination of multiple exposures effectively extends the dynamic range capability, achieving HDR效果 without requiring high-bit-depth encoders.
Solution Approach 2:
The system changes the exposure time parameter for different regions of the image rather than changing the bit depth parameter. By varying exposure time (a temporal parameter) across different spatial regions, the system achieves extended dynamic range capture while keeping the encoder's bit depth parameter at standard levels, thus resolving the contradiction between encoder capabilities and dynamic range requirements.
3Productivity
If network bandwidth is limited, then network efficiency is maintained, but transmission quality of HDR content is degraded
Solution Approach 1:
The system extracts only the essential information needed for high-quality HDR reproduction by selectively processing and transmitting data from different exposure regions. Rather than transmitting all raw data from multiple exposures, the system extracts and transmits only the critical information needed to reconstruct high-quality HDR video, reducing bandwidth requirements while maintaining transmission quality.
4Manufacturing precision
If multiple groups of pixels are captured at different exposure times, then dynamic range is improved, but device complexity and processing time are increased
Solution Approach 1:
The system dynamically adjusts exposure times for different pixel groups based on real-time scene analysis and importance weighting. Rather than using fixed exposure settings for all regions, the system dynamically determines optimal exposure times for each region, allowing it to achieve high dynamic range capture with adaptive processing that reduces unnecessary complexity in static or low-importance regions.
Data Source
AI summary
Systems and methods are provided for capturing high quality video data, including data having a high dynamic range, for use with conventional encoders and decoders. High dynamic range data is captured using multiple groups of pixels where each group is captured using different exposure times to create groups of pixels. The pixels that are captured at different exposure times may be determined adaptively based on the content of the image, the parameters of the encoding system, or on the available resources within the encoding system. The transition from single exposure to using two different exposure times may be implemented gradually.