Image Reshaping Pipeline for HDR and SDR Contrast Enhancement
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Solution Overview
Problem
Existing image processing technologies fail to effectively enhance dynamic range and local contrast in video content, leading to subdued viewing experiences on devices with varying display capabilities, such as HDR and SDR displays.
Innovation Solution
Implementing a combination of global and local reshaping operations, including forward and backward reshaping techniques, to enhance image dynamic range and local contrast, while preserving metadata and minimizing artifacts like false contouring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing image processing technologies are used, then processing simplicity is maintained, but dynamic range enhancement and local contrast improvement are insufficient
Solution Approach 1:
The image processing is divided into two distinct stages: global reshaping to enhance overall dynamic range, and local reshaping to improve local contrast. This segmentation allows each stage to focus on specific enhancement goals, achieving superior overall quality while maintaining manageable processing complexity through modular design.
Solution Approach 2:
Different reshaping strategies are applied to different regions of the image based on local characteristics. The local reshaping stage uses region-specific parameters and adaptive processing to enhance contrast in areas where it is most needed, while preserving global dynamic range improvements achieved in the first stage.
2Manufacturing precision
If aggressive reshaping operations are applied to enhance dynamic range, then viewing experience is improved, but artifacts like false contouring increase
Solution Approach 1:
The processing pipeline is designed to gradually build up enhancements across two stages rather than applying aggressive single-stage processing. This progressive approach cushions against the formation of false contouring artifacts by distributing the transformation load, allowing intermediate results to remain within acceptable quality thresholds.
Solution Approach 2:
The local reshaping stage operates with feedback from the global reshaping results, adapting its parameters to preserve enhancements while avoiding artifact generation. The system monitors and adjusts processing intensity based on local image characteristics to prevent false contouring.
3Manufacturing precision
If display-specific processing is applied to optimize for particular display types, then viewing quality on that display type is improved, but compatibility across different display types deteriorates
Solution Approach 1:
The dual-stage reshaping framework is designed as a universal processing pipeline that can be applied to any input image regardless of its intended display destination. The global and local reshaping operations work together to produce results that adapt well to various display characteristics, making the same processing approach effective for both HDR and SDR displays without requiring display-specific customization.
Data Source
AI summary
A first reshaping mapping is performed on a first image represented in a first domain to generate a second image represented in a second domain. The first domain is of a first dynamic range different from a second dynamic range of which the second domain is. A second reshaping mapping is performed on the second image represented in the second domain to generate a third image represented in the first domain. The third image is perceptually different from the first image in at least one of: global contrast, global saturation, local contrast, local saturation, etc. A display image is derived from the third image and rendered on a display device.