Patch Validity Test for Content-Aware Image Synthesis
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Solution Overview
Problem
Conventional content-aware fill tools are limited in identifying candidate patches, leading to suboptimal image completion quality, are computationally expensive, and lack user control over the sampling region and search domain, resulting in inconsistent and unnatural fill results.
Innovation Solution
An interactive system that allows users to specify a hole and sampling region, with a user interface for customizing fill properties like similarity transforms and color adaptation, and employs improved patch validity tests to efficiently synthesize content-aware fills using similarity transformed patches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional content-aware fill tools use randomized algorithms to identify approximate nearest neighbor matches, then fill synthesis can be performed automatically, but the computational complexity is high and the quality is suboptimal
Solution Approach 1:
The patent segments the image into patches and processes them individually through multiple stages (coarse-to-fine pyramid levels). Each patch is evaluated separately using the validity test, dividing the complex global optimization problem into manageable local decisions that can be processed efficiently in parallel.
Solution Approach 2:
The patent changes parameters by using similarity transforms (rotation, scaling, shearing) instead of only translation, and by processing at multiple resolution levels. This allows the system to find better matching patches while reducing the search space at each level, improving quality without linearly increasing computational complexity.
2Adaptability or versatility
If conventional tools use fixed sampling regions, then the system is simpler to implement, but user control is limited and results are inconsistent
Solution Approach 1:
The sampling region dynamically adapts based on user input through the constraint mask. Users can interactively modify which regions are valid for sampling, and the system responds by adjusting the patch search accordingly. This dynamic control enables adaptability while maintaining a relatively simple underlying algorithm structure.
Solution Approach 2:
The constraint mask acts as an intermediary between user intent and the patch-based synthesizer. It translates user specifications about desired and undesired sampling regions into a formal representation that the algorithm can process, providing user control without requiring complex direct manipulation of the synthesis algorithm.
3Measurement precision
If conventional tools perform comprehensive pixel-by-pixel validity testing, then patch validity is accurately determined, but the computational cost increases significantly
Solution Approach 1:
The validity test is segmented into three hierarchical stages: (1) quick rejection of patches with any pixel outside the sampling region, (2) validation of patches where all pixels are within the sampling region, and (3) handling of boundary cases. This segmentation allows most patches to be processed quickly while maintaining accurate validity determination for all patches.
Solution Approach 2:
The patent applies different validation strictness levels to different patches based on their location and characteristics. Patches clearly inside or outside the sampling region are handled with simple tests, while boundary patches receive more thorough validation. This local differentiation maintains accuracy where needed while improving overall processing speed.
Data Source
AI summary
Embodiments of the present invention provide systems, methods, and computer storage media for improved patch validity testing for patch-based synthesis applications using similarity transforms. The improved patch validity tests are used to validate (or invalidate) candidate patches as valid patches falling within a sampling region of a source image. The improved patch validity tests include a hole dilation test for patch validity, a no-dilation test for patch invalidity, and a comprehensive pixel test for patch invalidity. A fringe test for range invalidity can be used to identify pixels with an invalid range and invalidate corresponding candidate patches. The fringe test for range invalidity can be performed as a precursor to any or all of the improved patch validity tests. In this manner, validated candidate patches are used to automatically reconstruct a target image.