Image Inpainting Structure Strength Map Priority
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional image inpainting techniques fail to maintain structural continuity in images with unique non-repetitive structures, often resulting in artifacts during the restoration process.
Innovation Solution
A method and system that generate a structure strength map based on structural information within the restoration region, determining priority levels for pixels to ensure structural continuity by prioritizing inpainting operations according to these levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional inpainting techniques copy pixels from similar patches in nearby source regions, then the restoration process is simple and fast, but structural continuity is not maintained and artifacts appear in images with unique non-repetitive structures
Solution Approach 1:
The patent performs preliminary analysis of structural information in the image before executing the inpainting operation. A structure strength map is generated in advance to identify and prioritize structural regions, allowing the inpainting process to maintain structural continuity by guiding pixel copying based on pre-computed structural priorities rather than uniformly processing all regions.
Solution Approach 2:
The patent applies different inpainting strategies to different regions of the image based on their structural importance. By generating a structure strength map, the system identifies regions with strong structural characteristics and prioritizes them during inpainting, while less critical regions can be processed with simpler methods, thus maintaining overall structural continuity without uniformly increasing complexity across the entire image.
2Manufacturing precision
If pixel copying is performed without considering structural attributes, then the inpainting operation is computationally efficient, but artifacts are generated in restored regions
Solution Approach 1:
The structure strength map is computed in advance before the actual pixel copying operation. This preliminary analysis identifies which regions contain important structural information that must be preserved, allowing the inpainting algorithm to prioritize these regions and avoid copying operations that would disrupt structural continuity, thereby reducing artifacts while maintaining reasonable processing efficiency.
Solution Approach 2:
The patent introduces a new parameter (structure strength) that quantifies the importance of different image regions for structural continuity. By incorporating this parameter into the inpainting process, the system can dynamically adjust which pixels are copied and from where, improving restoration quality in structurally important regions while being more selective in less critical areas to maintain processing efficiency.
3Reliability
If all pixels in the restoration region are processed equally, then the inpainting process is simple to implement, but structural continuity cannot be maintained in regions with unique structures
Solution Approach 1:
The system performs preliminary analysis by generating a structure strength map that assigns priority levels to different pixels based on their structural importance. This pre-computation allows the subsequent inpainting process to selectively process pixels in a priority-driven manner, ensuring that structurally critical regions are handled with greater care while maintaining a relatively simple overall algorithm structure.
Solution Approach 2:
The patent applies differentiated processing to different pixels within the restoration region based on their local structural characteristics. Pixels with high structure strength values (indicating important structural information) are processed with higher priority and more careful selection of source patches, while pixels with lower structure strength can be processed more simply, thus maintaining structural continuity without uniformly increasing algorithmic complexity.
Data Source
AI summary
Various embodiments are disclosed for performing image inpainting. One embodiment is a method for editing a digital image in an image editing device that comprises obtaining a restoration region in the digital image and generating a structure strength map corresponding to the restoration region based on structure characteristics associated with each pixel in the restoration region. Based on the structure strength map, priority levels are determined for pixels in the restoration region. An inpainting operation is applied to the pixels in the restoration region, beginning with a pixel having a highest relative priority determined based on the structure characteristics.