LDR Image Dynamic Range Enhancement via Tone Mapping
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Solution Overview
Problem
Existing images and videos often have lower dynamic ranges than new high-performance display devices can handle, limiting the ability to fully utilize their capabilities and introducing noticeable artefacts.
Innovation Solution
A method that enhances lower-dynamic-range image data to produce higher-dynamic-range output, involving linearization of pixel values, contrast stretching, and application of a brightness enhancement function, which includes a smoothly varying component and an edge-stopping component to avoid artefacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If existing lower-dynamic-range image data is displayed on high-dynamic-range displays, then the display device capabilities are underutilized, but the image dynamic range is insufficient
Solution Approach 1:
The patent applies parameter changes by transforming the dynamic range parameters of LDR image data through linearization, contrast stretching, and tone mapping operations. This converts the intensity distribution parameters to match HDR display capabilities, enabling the display device to utilize its full dynamic range potential while displaying existing LDR content.
Solution Approach 2:
The patent introduces an intermediate processing stage that acts as a mediator between LDR image data and HDR displays. The processing pipeline including linearization, contrast stretching, and tone mapping serves as an intermediary transformation system that adapts the image data to bridge the gap between source and display capabilities.
2Illumination intensity
If contrast stretching is applied to enhance dynamic range, then the luminance range is expanded, but artefacts may be introduced
Solution Approach 1:
The patent applies local quality by implementing spatially varying contrast stretching where the enhancement factor is modulated by a smoothly varying function that adapts to local image characteristics. This ensures that contrast enhancement is applied differently across different regions, preserving edges and avoiding uniform artefact introduction.
Solution Approach 2:
The patent applies preliminary anti-action by pre-computing a contrast stretching function that incorporates edge detection and smoothing components before the actual contrast enhancement is applied. This preliminary preparation prevents artefacts by anticipating and compensating for potential edge-related issues before they manifest in the output image.
3Productivity
If real-time processing is performed to enhance dynamic range, then the processing speed is maintained, but the processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the dynamic range enhancement process into distinct modular stages: linearization, contrast stretching, and tone mapping. Each stage can be independently optimized and processed, enabling real-time performance through parallel processing or efficient sequential execution while managing overall complexity.
Solution Approach 2:
The patent applies preliminary action by pre-computing lookup tables and contrast stretching functions that can be rapidly applied during real-time processing. This preprocessing step reduces the computational burden during actual video frame processing, maintaining high processing speed while managing complexity through cached intermediate results.
Data Source
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AI summary
Methods and apparatus according to various aspects take as input image data in a lower-dynamic-range (LDR) format and produce as output enhanced image data having a dynamic range greater than that of the input image data (i.e. higher-dynamic range (HDR) image data). In some embodiments, the methods are applied to video data and are performed in real-time (i.e. processing of video frames to enhance the dynamic range of the video frames is completed at least on average at the frame rate of the video signal).