Image Vignetting Replacement Using Symmetry-Based Border Masks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional image generation systems rely on manual user identification of image vignetting, which is time-consuming and can result in unwanted loss of information or alteration of image size and shape when cropping is used to remove vignetting.
Innovation Solution
An image generation system that identifies a border mask based on symmetry and segmentation of a digital image, allowing it to distinguish and replace the vignetting area without manual user input, thereby generating a new image with extended content to fill the vignetting area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual user identification of border area is used, then accuracy of border detection is improved, but time consumption increases
Solution Approach 1:
The system performs automatic border area identification using symmetry analysis and segmentation algorithms, eliminating the need for manual user input. The border mask is generated autonomously by analyzing image characteristics, thus resolving the contradiction between accuracy and time consumption.
Solution Approach 2:
The system performs preliminary border detection and mask generation before the main image processing task. By pre-identifying the border area through symmetry and segmentation analysis, the system prepares the border mask in advance, reducing overall processing time while maintaining accuracy.
2Ease of manufacture
If cropping is used to remove border area, then border removal is simplified, but image content loss increases
Solution Approach 1:
The system segments the image into border area and content area using a generated border mask. This segmentation allows precise identification of border regions without affecting content areas, enabling border removal or replacement without cropping the entire image, thus preventing content loss while maintaining simplicity.
Solution Approach 2:
The system applies different processing to different regions: the border area is identified and processed separately from the content area using the border mask. This local differentiation ensures that only the border region is affected, preserving the quality and integrity of the content area while still achieving border removal.
3Ease of manufacture
If cropping is used to remove border area, then border removal is simplified, but image size and shape alteration occurs
Solution Approach 1:
By segmenting the border area using a generated border mask, the system can selectively process only the border region without affecting the overall image dimensions. This allows border removal while maintaining the original image size and shape, unlike cropping which alters the image boundaries.
Solution Approach 2:
The system applies border removal operations locally to the identified border area while preserving the content area and overall image dimensions. This localized processing maintains the original image size and shape while still achieving effective border removal.
Data Source
AI summary
Systems and methods for image generation are provided. An aspect of the systems and methods includes obtaining a digital image including a content area and a border area that includes at least two corners of the digital image; generating a border mask for the border area based on a symmetry of the border area with respect to the at least two corners; and generating a generated image based on the border mask, wherein the generated image includes the content area and a generated area corresponding to the border area, and wherein the generated area depicts an extension to content from the content area.