Selective Crosstalk Correction in Multiview Video
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Solution Overview
Problem
Multiview video processing technologies face challenges in reducing crosstalk and ghosting, which affect the quality of 3D video displays by causing incomplete isolation of image channels and subjective perception issues, particularly in regions with high disparity and intensity transitions.
Innovation Solution
The techniques involve identifying pixels with significant disparity and intensity transitions in co-located pairs of image frames and applying crosstalk correction using a 2D look-up table or equation-based processing, with location-based adjustment to tailor corrections to specific regions of the image frame, thereby reducing crosstalk and ghosting effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If crosstalk correction is applied to all pixels in multiview video frames, then 3D video quality is improved, but bandwidth and processing requirements increase significantly
Solution Approach 1:
The patent applies crosstalk correction selectively only to pixels that exhibit both high disparity and high intensity transitions, rather than uniformly to all pixels. This localized approach targets the specific regions where crosstalk is most problematic (edges and boundaries with significant depth differences) while leaving other pixels uncorrected, thereby reducing the overall bandwidth and processing requirements while maintaining 3D video quality in the critical regions.
2Manufacturing precision
If crosstalk correction is applied to all pixels in multiview video frames, then 3D video quality is improved, but processing complexity and computational burden increase
Solution Approach 1:
The patent implements a selective correction strategy that identifies and processes only the subset of pixels meeting both disparity and intensity transition thresholds. This local quality approach reduces processing complexity by avoiding unnecessary computations on pixels that do not require correction, while still achieving improved 3D video quality in the regions where it matters most.
Solution Approach 2:
The patent applies correction partially rather than completely - specifically targeting pixels with high disparity and high intensity transitions. This partial action principle allows the system to achieve sufficient 3D video quality improvement without the excessive processing complexity that would result from correcting all pixels, thereby resolving the contradiction between quality and processing burden.
3Manufacturing precision
If disparity threshold is set low to capture more crosstalk cases, then more regions are corrected, but false corrections increase in regions that don't need it
Solution Approach 1:
The patent combines two criteria - disparity threshold and intensity transition threshold - to identify pixels requiring correction. By merging these two conditions with a logical AND operation, the system ensures that only pixels satisfying both criteria are corrected. This combination prevents false corrections in regions with high disparity but low intensity transitions, while still achieving comprehensive coverage in regions where both conditions indicate crosstalk problems.
Solution Approach 2:
The patent uses adjustable threshold parameters for both disparity and intensity transitions. These parameters can be tuned to balance between correction coverage and accuracy depending on the specific application requirements. By changing these parameters, the system can adapt to different content types and display conditions, optimizing the trade-off between correcting enough regions and avoiding false corrections.
4Manufacturing precision
If intensity transition threshold is set low to capture more edges, then more pixels are corrected, but processing overhead increases
Solution Approach 1:
The patent employs an adjustable intensity transition threshold parameter that can be optimized based on the specific video content and application requirements. By tuning this parameter, the system can achieve good edge detection accuracy (capturing most pixels that need correction) while maintaining reasonable processing efficiency. The threshold can be adapted dynamically or set to a fixed value that balances detection accuracy with processing load.
Solution Approach 2:
The patent applies correction locally only to pixels that meet both the disparity and intensity transition criteria. Even when the intensity transition threshold is set low to capture more edges, the correction is applied selectively only to pixels that also have high disparity. This local quality approach ensures that processing overhead remains manageable by avoiding correction in regions where intensity transitions occur but disparity is low, thereby maintaining processing efficiency while achieving good edge detection accuracy.
Data Source
AI summary
In one example, a method includes identifying a first set of pixels in co-located pairs in a corresponding pair of multiview image frames for which the co-located pairs have a disparity between the pixels that is greater than a selected disparity threshold. The method further includes identifying a second set of pixels in at least one of the image frames that are within a selected distance of an intensity transition greater than a selected intensity transition threshold. The method further includes applying crosstalk correction to pixels that are identified as being in at least one of the first set and the second set.