Seamless Image Patch Matching via Multi-Characteristic Adjustment
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Solution Overview
Problem
In photo editing, users face challenges in seamlessly integrating objects from source images into target images due to differences in lighting intensity, color, noise levels, and gradient levels, which can result in unsatisfactory editing outcomes, even with techniques like Poisson Image Editing and Mean Value Cloning.
Innovation Solution
An image editing method that determines source and target regions, analyzes their characteristics, adjusts content to match the target image's characteristics, and applies smoothing or noise adjustment operations to ensure compatibility, using a system with a user interface generator, content analyzer, content modifier, and image synthesizer to insert the adjusted content into the target region.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If Poisson Image Editing or Mean Value Cloning is used to resolve lighting intensity and color level discrepancies, then lighting and color compatibility is improved, but noise level and gradient level mismatches remain causing visible boundaries
Solution Approach 1:
The patent applies parameter changes by adjusting multiple image characteristics including noise levels and gradient levels in addition to lighting and color. The system modifies these parameters to match between source and target images, resolving the boundary visibility issue that remained after traditional Poisson or Mean Value methods were applied alone.
2Productivity
If source patch is directly inserted into target image, then editing operation is simple and fast, but visible boundaries and unsatisfactory integration quality occur due to characteristic mismatches
Solution Approach 1:
The patent applies preliminary action by analyzing and adjusting image characteristics (lighting, color, noise, gradient) of the source patch before inserting it into the target image. This preprocessing step ensures compatibility between source and target, preventing visible boundaries and achieving seamless integration while maintaining editing efficiency.
3Manufacturing precision
If source region content is adjusted to match target image characteristics, then integration seamlessness is improved, but additional processing time and computational complexity are required
Solution Approach 1:
The patent systematically adjusts multiple image parameters (lighting intensity, color levels, noise levels, gradient levels) to achieve seamless integration. By comprehensively modifying these parameters, the system achieves high-quality seamless blending that matches all characteristic dimensions between source and target images.
Solution Approach 2:
The system employs feedback mechanisms by analyzing the target image characteristics and using this information to guide the adjustment of source region content. The analysis of lighting, color, noise, and gradient characteristics provides feedback that directs the modification process to achieve optimal seamless integration.
Data Source
AI summary
A method implemented in an image editing device comprises determining a source region in a source image and determining a target region in a target image. At least one image characteristic of each of the source region and a region outside the target region is analyzed. The content in the source region is adjusted according to the at least one image characteristic of the source region and the at least one image characteristic of the region outside the target region. The adjusted content from the source region is inserted into the target region.