Content-Adaptive Edge Enhancement for Image Sharpness and Noise Reduction
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Solution Overview
Problem
Existing edge and detail enhancement techniques for digital video processing, such as LTI/CTI and peaking, often introduce artifacts or fail to effectively enhance images with soft transitions or complex textures, particularly on human faces and in noisy environments.
Innovation Solution
A content-adaptive edge and detail enhancement algorithm that uses image analysis to create masks for controlling LTI/CTI and peaking techniques, incorporating a skin tone detection module to adjust LTI/CTI gain and applying negative coring to reduce noise in flat areas without compromising edge and detail enhancement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If LTI/CTI technique is used to steepen the Luma/Chroma transition slope, then image sharpness is improved, but unexpected artifacts and false contours are introduced
Solution Approach 1:
The patent applies different enhancement strengths to different regions of the image based on edge strength detection. Areas with strong edges receive higher LTI/CTI gain for sharpness enhancement, while areas with weak or no edges receive reduced or no enhancement to avoid artifacts. This local adaptation resolves the contradiction by making the enhancement quality-dependent rather than uniform.
Solution Approach 2:
The patent dynamically adjusts the LTI/CTI gain parameter based on the detected edge strength at each pixel location. The gain is not fixed but varies continuously based on local image characteristics, allowing the system to optimize sharpness where needed while avoiding artifacts in flat or texture-rich regions.
2Manufacturing precision
If peaking technique is used to amplify high frequency information, then image sharpness is improved, but noise is amplified in flat areas
Solution Approach 1:
The patent applies content-adaptive masking to control peaking operation. A mask is generated based on edge strength detection to identify regions where peaking should be applied (areas with edges and textures) versus regions where it should be suppressed (flat areas). This ensures high frequency amplification occurs only where it improves sharpness without amplifying noise in flat regions.
3Manufacturing precision
If LTI/CTI technique is applied to human faces, then edge transitions are steepened, but false contours are introduced on skin tones
Solution Approach 1:
The patent detects skin tone regions and applies reduced LTI/CTI gain specifically to those areas. By identifying the unique color characteristics of human skin and applying different enhancement parameters to those regions compared to other areas, the system preserves edge sharpness in non-face regions while avoiding false contours on faces.
Data Source
AI summary
A content-adaptive edge and detail enhancement apparatus is described for image/video processing. Both 2D peaking and LTI/CTI are used in sharpening pictures. Image analysis is performed to generate a blending factor to control the use of the two peaking techniques. The strength or likelihood of edges or transitions is measured and such a strength or likelihood measurement will be transformed into the blending factor controlling the blending of the LTI/CTI and peaking outputs.