Adaptive Image Upscaling with Geometry-Aware Edge Filtering
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Solution Overview
Problem
Conventional upscaling algorithms often result in visible artifacts and loss of image quality due to uniform filtering across the image plane, which fails to preserve details, especially around edges.
Innovation Solution
An adaptive upscaling algorithm that detects edges in images and applies different filter frequency responses based on local geometry, inserting additional pixels while preserving image details by generating filters with specific orientations to match edge directions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If uniform filters are applied across the image plane during upscaling, then aliasing artifacts are removed, but image details and edges become blurred
Solution Approach 1:
The patent applies different filter frequency responses to different regions of the image based on local geometry detection. Specifically, edges and non-edge regions are identified and processed with appropriate filters - preserving sharpness in edge regions while removing artifacts in non-edge regions. This local differentiation resolves the contradiction by making the filtering adaptive rather than uniform.
Solution Approach 2:
The patent dynamically adjusts filter selection based on detected edge directions and local image characteristics. The system changes filter parameters in real-time during processing, selecting from multiple filters with different frequency responses depending on the local geometry. This dynamic adaptation allows the system to maintain image details while removing artifacts.
2Area of stationary object
If additional pixels are inserted during upscaling to increase resolution, then image size increases, but visible artifacts are introduced
Solution Approach 1:
The patent performs geometry detection and filter selection before the actual pixel insertion and filtering operations. By pre-identifying edge locations and directions, the system prepares appropriate filters in advance, ensuring that when pixels are inserted and filtered, the correct local processing is applied to minimize artifact introduction while maintaining image quality.
3Measurement precision
If conventional upscaling algorithms are used to convert SD to HD format, then resolution increases, but image quality is lost
Solution Approach 1:
The patent preserves image quality during SD to HD conversion by applying local quality principles - different filter responses are applied to different regions based on detected geometry. This ensures that important image features like edges maintain their quality while still achieving the desired resolution increase, preventing the overall quality loss that occurs with conventional uniform filtering.
Data Source
AI summary
A system and method for scaling images are provided. An upscaling algorithm or function is employed that increases the size of an image and then filters the upscaled image to remove aliasing artifacts. The system and method provides for acquiring an image of a first size, detecting the geometry of the image, scaling the image to a second size, and filtering the scaled image with at least one filter based on the detected geometry. During the filtering process, the edges of objects in the upscaled image are detected and different filter frequency responses are provided for the detected edges. Providing different filter frequency responses for the detected edges preserves more details for line images.