Stereoscopic Video Encoding Disparity Control
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Solution Overview
Problem
Current stereoscopic video encoding systems for 3D content delivery suffer from poorly designed encoding solutions with subpar performance due to the lack of guidance on video encoding processes, leading to cross-contamination of image information and artifacts in stereoscopic displays.
Innovation Solution
A method to control encoding features based on disparity analysis, enabling or disabling encoding tools like de-blocking and motion compensation selectively across regions of an image pattern to prevent cross-contamination, using techniques such as bandpass filtering and motion estimation to classify disparity and prioritize encoding processes for regions with zero or low disparity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional monoscopic encoding methods are used for stereoscopic video, then compatibility with standard codecs is maintained, but cross-contamination between left and right views occurs causing artifacts
Solution Approach 1:
The patent applies local quality by differentiating encoding treatment between left and right views based on disparity magnitude. Regions with high disparity (foreground objects) use field-based encoding to prevent cross-contamination, while regions with low disparity (background) use frame-based encoding for better compression. This localized approach resolves the contradiction by applying different encoding strategies to different spatial regions.
Solution Approach 2:
The patent segments the stereoscopic video encoding process into disparity-based regions. By calculating disparity maps and classifying regions as high-disparity or low-disparity, the system segments the encoding approach into field-based and frame-based modes. This segmentation allows compatibility with standard codecs while preventing artifacts in critical high-disparity regions.
2Object-generated harmful factors
If field-based encoding is used for high disparity regions, then cross-contamination is prevented, but encoding complexity and computational load increase
Solution Approach 1:
The patent applies partial action by using field-based encoding only for high-disparity regions where it is necessary, rather than applying it globally to the entire stereoscopic video. The system calculates disparity maps and selectively applies field-based encoding only where needed, reducing overall encoding complexity while still preventing cross-contamination in critical areas.
Solution Approach 2:
The patent implements local quality by adapting the encoding strategy to local disparity characteristics. High-disparity regions use field-based encoding to prevent cross-contamination, while low-disparity regions use simpler frame-based encoding. This localized adaptation reduces overall encoding complexity while maintaining artifact prevention where necessary.
3Productivity
If frame-based encoding is used for low disparity regions, then compression efficiency is improved, but quality degradation occurs in high disparity regions
Solution Approach 1:
The patent applies local quality by differentiating encoding treatment between high-disparity and low-disparity regions. Low-disparity background regions use frame-based encoding for better compression efficiency, while high-disparity foreground regions use field-based encoding to prevent cross-contamination artifacts. This resolves the contradiction by optimizing compression where safe and preventing artifacts where critical.
Solution Approach 2:
The patent uses partial action by applying frame-based encoding (which provides better compression) only to low-disparity regions where it is safe to do so. High-disparity regions receive field-based encoding to prevent artifacts. This partial application of frame-based encoding improves overall compression efficiency without sacrificing quality in critical areas.
4Manufacturing precision
If disparity-based regional encoding control is implemented, then encoding quality is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by performing disparity map calculation and region classification before the actual encoding process. By pre-segmenting the video into high-disparity and low-disparity regions, the system prepares encoding parameters in advance, allowing the main encoding process to proceed efficiently without real-time decision-making delays.
Solution Approach 2:
The patent uses partial action by applying complex disparity-based analysis only where necessary to classify regions, rather than performing exhaustive analysis on every pixel throughout the entire encoding process. This selective approach improves encoding quality while limiting additional processing time to essential region classification tasks.
Data Source
AI summary
Controlling a feature of an encoding process for regions of an image pattern representing more than one image when the regions include an amount of disparity in the represented images that would result in cross-contamination between the represented images if encoded with the feature. The control may be, for example, any of, turning the encoding feature off, using the encoding feature less often than when encoding an image pattern representing a single image, negatively biasing the encoding feature, and enabling the encoding feature for regions determined to have zero or near zero disparity and disabling the feature for all other regions. The represented images comprise, for example, any of a stereoscopic view, multiple stereoscopic views, multiple views of a same scene, and multiple unrelated views.