Variable Patch Shape Synthesis for Depth Discontinuity Handling
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Solution Overview
Problem
Conventional patch synthesis techniques using fixed-shaped patches are limited in accurately representing image regions, especially when dealing with multiple depth layers and parallax issues, leading to suboptimal synthesis results in applications like hole-filling and image matching.
Innovation Solution
The implementation of variable patch shape synthesis techniques, where patches with different shapes are computed and used in a patch search and vote process, leveraging content adaptive masks and machine learning to select appropriate masks and nearest neighbor fields for improved synthesis, particularly in handling depth discontinuities and edge cases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed-shaped patches are used in patch synthesis, then the implementation is simple and computationally efficient, but the accuracy of representing image regions deteriorates
Solution Approach 1:
The patent transforms fixed-shaped patches into dynamic variable-shaped patches that can adapt their boundaries to match image content. The mask-based approach allows patches to dynamically adjust their shape to include only relevant image regions, resolving the contradiction between implementation simplicity and representation accuracy.
Solution Approach 2:
The patent applies different shapes and masks to different patches based on their local image content requirements. Each patch can have a customized shape that optimally represents its specific region, allowing local adaptation while maintaining overall system efficiency through the unified mask framework.
2Measurement precision
If variable patch shapes are used in patch synthesis, then the accuracy of representing image regions improves, but the computational complexity increases
Solution Approach 1:
The patent performs preliminary computation of variable patch shapes and their masks before the actual synthesis process. By pre-computing the optimal shapes and storing them, the system avoids repeated complex calculations during synthesis, thus improving accuracy while managing computational complexity through advance preparation.
Solution Approach 2:
The patent segments the image into multiple variable-shaped patches with different masks, allowing independent optimization of each patch shape. This segmentation approach distributes the computational complexity across multiple smaller, manageable units rather than requiring complex global optimization.
3Reliability
If variable patch shapes are used in patch synthesis, then the handling of depth layers and edge cases improves, but the processing time increases
Solution Approach 1:
The patent applies local quality by using content-adaptive masks that specifically target regions with depth discontinuities and edge cases. These masks concentrate processing resources on problematic areas while using simpler representations for uniform regions, improving depth layer handling without proportionally increasing overall processing time.
Data Source
AI summary
Variable patch shape synthesis techniques are described. In one or more implementations, a plurality of patches are computed from one or more images, at least one of the plurality of patches having a different shape than another one of the plurality of patches. The shapes define an area to be considered for use in a patch synthesis technique. The patch synthesis technique is performed to edit an image using the computed plurality of patches having the different shapes.