HDR Image Editing Visualizations for Device-Aware Luminance Mapping
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Solution Overview
Problem
Conventional high dynamic range (HDR) techniques for digital images face inconsistencies and reduced functionality due to variations in display device capabilities and environmental conditions, leading to decreased accuracy and reduced contrast across different devices and environments.
Innovation Solution
A high dynamic range editing system generates configurable visualizations, such as histograms, capability indicators, point curves, and previews, to assist in editing HDR images, accounting for device and environmental capabilities, enabling precise luminance adjustments and conversions between HDR and standard dynamic range (SDR).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional HDR techniques are used across different display devices, then HDR functionality is achieved, but inconsistencies and reduced functionality occur due to device variations
Solution Approach 1:
The system changes the parameters of HDR visualization by generating multiple representations (histograms showing luminance distribution, capability indicators showing device-specific HDR support, point curves showing tone mapping). These different parameter representations allow the same HDR image to be appropriately displayed across devices with varying capabilities, resolving the contradiction between consistency and adaptability.
2Measurement precision
If HDR editing is performed without device-specific visualizations, then editing process is simplified, but accuracy decreases due to inability to account for device capabilities
Solution Approach 1:
The patent introduces intermediary visualizations (histograms, capability indicators, point curves) that mediate between the HDR image data and the final device-specific output. These intermediaries provide accurate luminance information without requiring complex direct device-specific editing workflows, thus improving precision while managing complexity.
3Manufacturing precision
If multiple visualization types are generated for HDR editing, then editing precision is enhanced, but system complexity increases
Solution Approach 1:
The system segments the HDR editing visualization into distinct functional components: histograms for luminance distribution analysis, capability indicators for device-specific parameter verification, and point curves for tone mapping control. This segmentation allows each visualization type to serve a specific precision function without requiring the entire system to be overly complex.
Data Source
AI summary
A high dynamic range editing system is configured to generate visualizations to aide digital image editing in both high dynamic ranges and standard dynamic ranges. In a first example, the visualization is generated as a histogram. In a second example, the visualization is generated to indicate high dynamic range capabilities. In a third example, the visualization is generated to indicate ranges of luminance values within a digital image. In a fourth example, the visualization is generated as a point curve that defines a mapping between detected luminance values from a digital image and output luminance values over both a standard dynamic range and a high dynamic range. In a fifth example, the visualization is generated as a preview to convert pixels from the digital image in a high dynamic range into a standard dynamic range.