Color Balancing Using Reference Points for Real-Time Video
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Solution Overview
Problem
Conventional color balancing techniques are inadequate for real-time applications and require manual user input, failing to effectively match coloration between images or video streams captured under varying lighting conditions, leading to distortions in composited video streams.
Innovation Solution
A method and system that adjust coloration by determining coloration differences between reference points in images or video streams and applying these differences to ensure consistent color balancing, using visual characteristics information to match the coloration of virtual objects to that of real-world objects under neutral lighting conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual user input is used for color balancing, then coloration can be adjusted, but the process is not suitable for real-time applications and requires user intervention
Solution Approach 1:
The system automatically performs color balancing by selecting reference points and determining coloration differences without requiring manual user input. The processor autonomously identifies corresponding reference points in first and second images, calculates coloration differences, and adjusts the first image's coloration to match the second image, enabling real-time processing while maintaining accurate color matching
Solution Approach 2:
The system pre-establishes a mapping relationship between reference points in different images before actual color balancing is needed. By storing the correspondence between reference points and their coloration characteristics in advance, the system can quickly retrieve and apply these mappings during real-time operations without performing complex calculations at runtime
2Ease of manufacture
If predetermined color balancing operations are applied, then coloration can be adjusted, but the adjustments may not match the specific coloration differences between images
Solution Approach 1:
The system dynamically determines coloration parameters by comparing actual reference points from the first and second images. Instead of applying fixed predetermined operations, the processor calculates specific coloration differences (such as hue, saturation, and brightness variations) between corresponding reference points and applies these customized adjustments to achieve precise color matching tailored to each image pair
3Reliability
If camera-level alterations are applied to optimize visual factors, then image quality is improved, but these alterations do not apply to virtual objects and cause distortions in composited video streams
Solution Approach 1:
The system applies color balancing adjustments uniformly to both real-world captured images and virtual objects inserted into the scene. By determining coloration differences from reference points in the captured image and applying these same adjustments to composite the video stream, the system ensures that both real and virtual elements share consistent color characteristics, eliminating distortions while maintaining optimization under varying lighting conditions
Data Source
AI summary
Embodiments provide techniques for adjusting coloration of an image. A first selection of first one or more reference points within a first image is received. A second selection of a second one or more reference points within a second image is also received. Embodiments determine a coloration difference between a coloration of the first one or more reference points within the first image and a coloration of the second one or more reference points within the second image. The coloration of at least a portion of the first image is then adjusted, based on the determined coloration difference.