Video Brightness Matching via MCU Sampling
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Solution Overview
Problem
In multipoint videoconferencing, differences in brightness levels among video images from various endpoints can disrupt user experience, particularly in video switching and continuous presence modes, due to varying brightness conditions and camera settings, leading to unpleasant transitions and difficulty in viewing all conferees simultaneously.
Innovation Solution
Implementing a system with brightness sampling and analyzing modules (BSAM) and transforming logical modules (TLM) within a multipoint control unit (MCU) to calculate and adjust brightness levels across video images, using algorithms like average brightness calculation or histogram analysis, and applying brightness transformation functions to ensure consistent perceptual brightness across all images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video images from multiple endpoints with different brightness conditions are displayed, then the system can support diverse lighting environments, but the brightness levels become inconsistent causing user discomfort and difficulty in viewing
Solution Approach 1:
The system automatically adjusts brightness parameters of video images by calculating average brightness values and applying transformation functions. The MCU modifies brightness levels dynamically to ensure consistent appearance across all conferee images, resolving the contradiction between supporting diverse lighting conditions and maintaining brightness consistency.
2Ease of operation
If brightness levels are not adjusted, then the system operation remains simple, but user adaptation time increases and viewing comfort decreases
Solution Approach 1:
The brightness adjustment system operates automatically without requiring manual user intervention. The MCU independently calculates brightness parameters, determines transformation functions, and applies corrections to video images, eliminating the need for user configuration while reducing adaptation time and improving viewing comfort.
3Illumination intensity
If manual brightness adjustment is required for each endpoint, then brightness consistency can be achieved, but the system complexity and operational difficulty increase
Solution Approach 1:
The MCU acts as an intermediary that centralizes brightness control functionality. Instead of requiring manual configuration at each endpoint, the MCU receives video images, calculates appropriate brightness transformations, and applies corrections automatically, simplifying the overall system while maintaining brightness consistency across all conferees.
Data Source
AI summary
Methods and systems for presenting video images generated by multiple endpoints in a videoconference such that the displayed images have consistent appearance, for example consistent brightness levels are disclosed. Sampling methods and algorithms are used to calculate an appropriate amount of correction for each video image and the images are adjusted accordingly. Brightness correction may implement one or more brightness sampling and analyzing logical modules (BSAM) and one or more transforming logical module (TLM). The brightness matching methods may be implemented in centralized architecture, for example, as part of a multipoint control unit (MCU). Alternatively, the methods may be implemented using a distributed architecture.