LDR to HDR Image Conversion Saturation Region Adjustment
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Solution Overview
Problem
Existing digital imaging systems face challenges in converting low dynamic range (LDR) images to high dynamic range (HDR) representations, particularly in handling saturation regions where image information is lost, leading to a need for methods that can effectively adjust color model values to reconstruct lost data and enhance image quality.
Innovation Solution
A method that identifies pixels in saturation regions and adjusts their color model values based on characteristics such as distance from the saturation edge, region size, gradient, temporal behavior, and lens flare patterns, using scaling and offset techniques to create a higher bit depth representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If simple linear scaling techniques are used to convert LDR images to HDR representations, then the conversion process is simple and fast, but the quality of the converted image deteriorates due to loss of image information in saturation regions
Solution Approach 1:
The patent segments the image processing into distinct stages: identifying saturation regions, determining adjustment amounts based on distance from saturation edges, and applying differential adjustments to restore lost image information. This segmentation allows complex image restoration while keeping each processing stage manageable.
Solution Approach 2:
The patent applies local quality by adjusting color model values differently based on local characteristics - specifically, pixels closer to saturation edges receive different adjustment amounts than pixels farther from edges. This localized adjustment restores image information where needed while preserving areas that don't require restoration.
2Adaptability or versatility
If LDR systems are used, then device complexity is reduced and compatibility is maintained, but the ability to represent and display high dynamic range images deteriorates
Solution Approach 1:
The patent applies preliminary action by converting LDR images to HDR representations before display or further processing. This preliminary conversion enables HDR systems to utilize existing LDR image sources, bridging the gap between legacy content and modern HDR capabilities without requiring complete system replacement.
Solution Approach 2:
The patent changes parameters by transforming color model values from LDR bit depth to HDR bit depth, adjusting saturation thresholds, and modifying adjustment amounts based on distance metrics. These parameter changes enable the system to handle both LDR and HDR representations, providing adaptability across different dynamic range requirements.
3Loss of information
If saturation regions are not adjusted, then processing time is reduced and simplicity is maintained, but loss of information in saturation regions persists
Solution Approach 1:
The patent introduces an intermediary process between simple scaling and full image restoration: identifying saturation regions and applying distance-based adjustment amounts. This intermediary approach recovers lost image information in saturation regions while avoiding the computational burden of complete image reconstruction, balancing information recovery with processing efficiency.
Data Source
AI summary
Aspects of the invention provide systems and methods for converting a digital image represented in a lower bit depth representation to a higher bit depth representation. A saturation region is identified, where a color model value of the pixels in the saturation region is above an upper saturation threshold or below a lower saturation threshold. The color model value for each pixel in the saturation region is then adjusted by a corresponding adjustment. The magnitude of the adjustment for each pixel is based on characteristics of the image data.