Frequency Lifting Super-Resolution for Image Sharpness
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Solution Overview
Problem
Ultra-high definition (UD) displays struggle to maintain image quality when displaying lower resolution content, such as standard definition (SD) or high-definition (HD) videos, as regular image upscaling or interpolation fails to provide sufficient sharpness and fine details, leading to degraded image quality.
Innovation Solution
A method involving a processor device that determines enhancement information based on frequency characteristics and feature information of the input image, which is then mixed with the input image to generate an enhanced image, utilizing an image feature detection module, a control gain map estimation/generator module, and a frequency lifting super-resolution module to reduce potential image artifacts and improve sharpness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If regular image upscaling or interpolation is used, then the display can show lower resolution content on UD devices, but the image sharpness and fine details are insufficient leading to degraded image quality
Solution Approach 1:
The patent applies parameter changes by adjusting frequency characteristics and gain control values dynamically. The frequency lifting super-resolution process modifies frequency parameters to enhance high-frequency components, while gain control adjusts the strength of enhancement based on local image features, thereby improving sharpness and fine details without sacrificing compatibility with lower resolution content
Solution Approach 2:
The patent transitions from spatial domain processing to frequency domain processing by applying frequency lifting. This dimensional change allows the system to enhance high-frequency information that is lost in low-resolution content, adding fine details and sharpness in the frequency domain before transforming back to spatial domain for display
2Manufacturing precision
If frequency lifting super-resolution is applied to enhance image details, then image sharpness improves, but image artifacts may be introduced
Solution Approach 1:
The patent applies local quality by using gain control based on local image features. Different regions of the image are processed with different gain values according to their specific characteristics (e.g., texture, edge, smooth regions). This localized approach enhances sharpness where needed while suppressing artifacts in regions where frequency lifting would create harmful effects, such as in homogeneous areas or regions with strong edges
Solution Approach 2:
The patent implements feedback through the gain control mechanism that uses detected image features to dynamically adjust processing parameters. The system continuously monitors image characteristics and adjusts the frequency lifting strength accordingly, reducing artifacts when the enhancement would be detrimental and maintaining sharpness when beneficial
Data Source
AI summary
Input image information is received. A processor device is used for determining enhancement information based on frequency characteristics and feature information of the input image information. The enhancement information is mixed with the input image information to generate an enhanced image.