Super Resolution Sharpening Gain Control for Graphics Images
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Solution Overview
Problem
Existing image processing technologies face significant degradation when sharpening is applied to graphics images, as it emphasizes noise and degrades the image quality, especially when converting standard definition to higher resolutions.
Innovation Solution
An image processing apparatus and method that includes a scaling converter, luminance histogram detector, determination module, and super resolution processor, which detects graphics images based on luminance histograms and adjusts the sharpening gain to prevent noise enhancement by setting it lower than the reference gain when a graphics image is identified.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If sharpening is performed on an input image after scaling to increase resolution, then the resolution is enhanced, but noise is emphasized and image quality degrades significantly in graphics images
Solution Approach 1:
The patent applies different sharpening gains to different types of images by detecting whether the input image is a natural image or graphics image using luminance histogram analysis. For natural images, a higher sharpening gain is applied to enhance resolution, while for graphics images, a lower sharpening gain is applied to avoid noise emphasis. This local differentiation resolves the contradiction by tailoring the sharpening strength to the specific image type.
Solution Approach 2:
The patent changes the sharpening parameter (gain value) based on the detected image type. When a graphics image is detected through luminance histogram analysis, the sharpening gain is reduced to prevent noise emphasis. When a natural image is detected, the sharpening gain is increased to achieve resolution enhancement. This dynamic parameter adjustment resolves the contradiction between resolution enhancement and noise control.
2Manufacturing precision
If sharpening gain is increased to enhance resolution effect, then resolution enhancement is improved, but noise occurs in pixels increased to enhance resolution
Solution Approach 1:
The patent detects the image type using luminance histogram analysis and applies different sharpening gains locally. For graphics images where noise is problematic, a lower sharpening gain is applied. For natural images where resolution enhancement is prioritized, a higher sharpening gain is applied. This local quality differentiation resolves the contradiction between resolution enhancement effect and noise control in increased pixels.
Data Source
AI summary
According to one embodiment, an image processing apparatus includes a scaling converter, a luminance histogram detector, a determination module, and a super resolution processor. The scaling converter converts a first image signal to a second image signal having more pixels. The luminance histogram detector detects a luminance histogram. The determination module determines whether the second image signal includes a graphics image based on the luminance histogram. The super resolution processor converts the second image signal to a third image signal with a higher resolution than that of the second image signal, and performs sharpening based on the reference gain. When the second image signal includes a graphics image, the super resolution processor sets the gain of sharpening below the reference gain.