Context-Aware Image Scaling for Artifact Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Image scaling technologies often result in visual artifacts such as blurring and ringing around the edges of objects due to the interpolation of pixel values, especially when upscaling or downscaling images for display on devices with different resolutions.
Innovation Solution
The implementation of context-aware interpolation (CAI) that leverages transparency values in image data to fine-tune pixel interpolation, reducing the need for additional context detection and providing a cost-effective and simple method to minimize artifacts by using transparency information to differentiate between image sources and objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional image scaling is used to convert images between resolutions, then the display can show images on devices with different resolutions, but visual artifacts such as blurring and ringing appear around object edges
Solution Approach 1:
The patent applies different interpolation strategies to different regions of the image based on transparency values. Pixels with transparency values indicating overlay content use one interpolation method, while opaque pixels use another. This local differentiation allows the system to preserve sharp edges in opaque regions while properly blending semi-transparent regions, eliminating the visual artifacts that occur when a single interpolation method is applied uniformly across the entire image.
2Manufacturing precision
If transparency values are used to differentiate image sources and objects for interpolation, then visual artifacts are reduced and edges are sharper, but the processing complexity increases
Solution Approach 1:
The patent leverages transparency values that are already present in the image data from graphics generation, rather than requiring separate context detection mechanisms. The transparency information, which is inherently available in the image pipeline for overlay and blending operations, is repurposed to guide the interpolation process. This self-service approach allows the system to achieve context-aware interpolation without adding complex external detection systems, thus improving edge sharpness while minimizing increases in processing complexity.
Data Source
AI summary
A method and apparatus for image processing. An image scaling circuit is configured to receive image data for a plurality of pixels corresponding to a first image. The image data includes color information and a transparency value for each of the plurality of pixels. The image scaling circuit updates the image data by selectively changing the color information for one or more of the pixels based at least in part on the transparency values. In updating the image data, the image scaling circuit may determine contextual information about the first image based at least in part on the transparency values. The image scaling circuit further generates an interpolated image based on the updated image data for the plurality of pixels. For example, the interpolated image may be a scaled version of the first image.