Chroma Reconstruction via Content-Adaptive Up-Sampling
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Solution Overview
Problem
Current methods for chroma reconstruction in video content, especially for synthetic screen content, suffer from artifacts and inefficiencies due to the lack of hardware acceleration for YUV 4:4:4 sub-sampling and the inability of existing adaptive up-sampling techniques to handle the specific characteristics of screen content, leading to image degradation and increased bandwidth usage.
Innovation Solution
A method and apparatus that utilize a decoder and an up-sample filter to analyze and select reconstruction algorithms based on content type, identifying homogeneous luma components to reconstruct chroma components efficiently, and normalizing luma components to scale chroma components when gradients are present, allowing for efficient chroma prediction and reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If guided image filter is used to reconstruct chroma components, then edge preservation is improved, but artifacts are introduced in synthetic screen content
Solution Approach 1:
The patent applies different reconstruction strategies to different regions of the image based on content type detection. For synthetic screen content, it uses a specialized algorithm that preserves sharp edges and homogeneous regions, while for natural content, it uses traditional guided filtering. This local adaptation eliminates artifacts in screen content while maintaining edge preservation in natural content.
Solution Approach 2:
The patent changes the reconstruction parameters and algorithm selection based on detected content type. When synthetic screen content is detected, it adjusts the chroma reconstruction parameters to handle sharp discontinuities and homogeneous colors, whereas it uses standard parameters for natural content. This parameter adaptation resolves the contradiction between edge preservation and artifact reduction.
2Manufacturing precision
If YUV 4:4:4 chroma sub-sampling is implemented, then image quality is improved, but hardware acceleration is unavailable and cost increases
Solution Approach 1:
The patent uses the luma component as a guide to copy and reconstruct the chroma component. By analyzing the luma structure and using it to infer chroma values, the system achieves high-quality chroma reconstruction without requiring expensive hardware acceleration for YUV 4:4:4 processing. This copying approach maintains image quality while using standard hardware.
3Manufacturing precision
If existing adaptive up-sampling techniques are used, then chroma reconstruction is improved, but they fail to handle synthetic screen content characteristics
Solution Approach 1:
The patent detects content type (synthetic screen content vs. natural content) and applies locally optimized reconstruction algorithms. For synthetic content with sharp edges and homogeneous regions, it uses a specialized algorithm, while for natural content, it uses traditional adaptive up-sampling. This local quality approach resolves the contradiction between reconstruction quality and content adaptability.
Data Source
AI summary
A method and apparatus for predicting chroma values including the steps of having a decoder provide an image frame to an up-sample filter, the image frame having luma and chroma components, and applying an analysing algorithm on a subset of said image frame to obtain the subset content type, and, depending on the content type, select a reconstruction algorithm to reconstruct the chroma components.