Cross-Asset HDR Chroma Reformatting With Guided Filtering
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Solution Overview
Problem
Existing image processing technologies struggle to effectively upsample chroma components in high dynamic range (HDR) images to match the quality of lower dynamic range (SDR) images within a multi-asset imaging format, leading to artifacts and suboptimal display quality.
Innovation Solution
Implement guided filtering that utilizes spatial resolution information from luma and chroma components of lower dynamic range images to enhance chroma components of higher dynamic range images, ensuring high-quality chroma upsampling through a guided filtering framework.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If chroma components of HDR images are upsampled using conventional methods, then the chroma resolution is improved, but artifacts and suboptimal display quality occur
Solution Approach 1:
The patent applies guided filtering before final chroma upsampling to pre-process the chroma components. This preliminary filtering operation removes potential artifacts and prepares the chroma data for high-quality upsampling, preventing artifact propagation through the processing pipeline
Solution Approach 2:
The patent introduces luma components as an intermediary guide in the chroma upsampling process. The luma information serves as a mediator that provides spatial and frequency domain guidance to upscale chroma components without introducing artifacts, as luma contains edge and texture information that helps preserve chroma boundaries
2Adaptability or versatility
If chroma sampling format of HDR images is changed to match SDR images, then display compatibility is improved, but processing complexity increases
Solution Approach 1:
The patent transforms chroma sampling parameters (format, resolution, subsampling ratio) to match between HDR and SDR images. By systematically changing these parameters through guided filtering and resampling operations, the patent achieves display compatibility while managing processing complexity through efficient algorithmic approaches
3Manufacturing precision
If guided filtering is applied to upsample chroma components, then visual quality is improved, but computational requirements increase
Solution Approach 1:
The patent segments the guided filtering process into distinct stages: luma-guided chroma filtering, chroma upsampling, and final composition. This segmentation allows for optimized processing at each stage, reducing overall computational requirements while maintaining high visual quality through targeted operations
Data Source
AI summary
A first image and a second image of different dynamic ranges are derived from the same source image. Based on a chroma sampling format of the first image, it is determined whether edge preserving filtering is to be used to generate chroma upsampled image data in a reconstructed image. If so, image metadata for performing the edge preserving filtering is generated. The first image, the second image and the image metadata are encoded into an image data container to enable a recipient device to generate the reconstructed image.