Dual-Stream Image Processing for VR Color Consistency
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Solution Overview
Problem
Existing image processing systems struggle to integrate dual-field-of-view (FOV) image streams effectively, particularly in VR and AR applications, due to discrepancies in color, brightness, and dynamic range, which are exacerbated by different processing techniques and lighting conditions, leading to inconsistent and unrealistic user experiences.
Innovation Solution
A method and system that processes wide and narrow FOV image streams using a first processing technique, stores crucial image attributes, and employs a neural network to enhance the narrow FOV stream, ensuring color and dynamic range consistency, followed by blending to generate a coherent final image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If different processing techniques are used for wide and narrow FOV image streams, then each stream can be optimized for its specific characteristics, but color and brightness consistency between streams deteriorates
Solution Approach 1:
The patent introduces an intermediary processing stage where the first processed image stream serves as a reference to guide the processing of the second image stream. This mediator approach allows different processing techniques to be applied initially, then uses the first stream's processed characteristics (color, brightness, dynamic range) as reference standards to adjust and synchronize the second stream, resolving the consistency issue while maintaining processing efficiency
Solution Approach 2:
The patent dynamically adjusts processing parameters (such as exposure time, gain, white balance) of the second image stream based on real-time analysis of the first stream's processed output. By changing these parameters adaptively, the system maintains color and brightness consistency between streams even when different base processing techniques are used, thus resolving the contradiction between processing optimization and visual consistency
2Manufacturing precision
If manual adjustments are made to synchronize image streams, then color and brightness consistency improves, but processing time and system complexity increase
Solution Approach 1:
The system implements self-service by automatically analyzing the first processed image stream and using its characteristics to guide the processing of the second stream without requiring manual intervention. The processor autonomously adjusts parameters, applies tone mapping, and synchronizes visual properties, achieving high visual consistency while avoiding the complexity and time consumption of manual adjustments
Solution Approach 2:
The patent establishes a feedback loop where the processed first image stream continuously informs the processing parameters of the second stream. This real-time feedback mechanism allows the system to automatically maintain visual consistency across varying lighting conditions and scenes without manual intervention, reducing both system complexity and processing time compared to manual methods
3Speed
If simplistic blending techniques are used to combine image streams, then processing speed improves, but visual coherence and realism deteriorate
Solution Approach 1:
The patent applies preliminary action by processing and synchronizing the first image stream completely before using it as a reference for the second stream. This preliminary processing establishes accurate color, brightness, and dynamic range baselines that guide subsequent blending operations, ensuring visual coherence is built into the combination process rather than attempted afterward, thus maintaining both speed and quality
4Adaptability or versatility
If real-time processing is implemented to adapt to changing conditions, then adaptability improves, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the dual-FOV image processing into distinct stages: first processing the wide FOV stream to establish reference characteristics, then using those references to guide narrow FOV stream processing. This segmentation allows real-time adaptability to be achieved through a manageable sequence of operations rather than attempting simultaneous complex processing of all parameters, thus improving adaptability while controlling computational complexity
Data Source
AI summary
Disclosed is a method and an apparatus for processing dual-stream images. The method includes processing a wide field-of-view (FOV) image stream using a first processing technique. The method further includes storing one or more of color information, gamma or tone mapping information, semantic information from the wide FOV image stream. The method further includes processing a narrow FOV image stream using a neural network based on the one or more of the white balance information, the gamma or tone mapping information, and semantic information. The method further includes blending the processed wide FOV image stream and the processed narrow FOV image stream to generate a final image, for display on a display device.