Motion Map Upsampling Using Color Transition Detection
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Solution Overview
Problem
Conventional methods lack the ability to intelligently modify the resolution or accuracy of auxiliary maps, such as motion maps, by considering their distinctive topological characteristics and additional information, which is crucial for maintaining accuracy at transitions between homogeneous areas with sharp discontinuities.
Innovation Solution
The approach involves generating motion maps at multiple levels of quality by using color transition information and meta-data to refine motion vectors, allowing for novel upsampling operations that create higher-resolution maps while maintaining accurate representations of motion across different levels of quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional motion estimation techniques are used, then the complexity of estimating accurate motion maps is reduced, but the precision and accuracy of motion maps at transitions between homogeneous areas deteriorate
Solution Approach 1:
The patent applies local quality by differentiating processing between homogeneous areas and transition regions. Motion vectors in homogeneous areas are generated through standard interpolation, while transition regions are identified using color transition information and processed separately to preserve sharp discontinuities. This selective approach improves motion map accuracy at boundaries without uniformly increasing complexity across the entire image.
Solution Approach 2:
The patent changes parameters by introducing color transition information and meta-data as additional inputs to the motion estimation process. By detecting color transitions and using this information to guide motion vector generation, the system achieves higher precision at transitions while maintaining manageable complexity through parameter-based differentiation rather than computationally intensive methods.
2Manufacturing precision
If motion maps are upsampled from lower to higher resolution, then the detail and accuracy of motion information is improved, but the complexity of processing and maintaining accuracy at discontinuities increases
Solution Approach 1:
The patent applies preliminary action by pre-identifying transition regions using color transition information before the upsampling process. By detecting where sharp discontinuities exist in advance and marking these regions, the upsampling algorithm can then apply appropriate processing only where needed, rather than uniformly processing the entire high-resolution map. This reduces processing complexity while maintaining accuracy at critical boundaries.
Solution Approach 2:
The patent uses color transition information and meta-data as intermediary elements that guide the upsampling process. These intermediaries carry information about where sharp transitions occur, allowing the upsampling algorithm to intelligently adjust its behavior in different regions. This mediator approach enables high-resolution reconstruction without requiring complex global processing, as the intermediaries provide localized guidance.
3Productivity
If standard interpolation techniques are used for upsampling, then the processing is simple and fast, but the accuracy at transitions between homogeneous areas with sharp discontinuities deteriorates
Solution Approach 1:
The patent applies local quality by using color transition information to identify transition regions and applying different processing strategies to different areas. In homogeneous areas, simple and fast interpolation methods are used, while in transition regions, the algorithm preserves sharp discontinuities by leveraging the detected color transition boundaries. This localized approach maintains high productivity overall while improving accuracy where it matters most.
Solution Approach 2:
The patent segments the image into homogeneous areas and transition regions based on color transition detection. This segmentation allows the system to apply appropriate processing to each segment: fast interpolation in homogeneous areas and boundary-preserving processing in transition regions. The segmentation approach enables the system to achieve high accuracy at transitions without sacrificing overall processing speed.
Data Source
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AI summary
Certain configurations herein include changing the resolution of an auxiliary map (e.g., a motion map, a z-map, etc.) at a first level of quality to obtain an auxiliary map at a second level of quality. For example, changing the resolution can include receiving a respective auxiliary map of one or more vectors at one or more lower levels of quality and progressively refining, via novel operations, the auxiliary map to higher or lower levels of quality in a hierarchy.