Image Processing Tone Curve Adjustment for HDR Display Accuracy
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Solution Overview
Problem
Current display technologies face challenges in efficiently displaying high dynamic range (HDR) images, as they often require complex encoding and decoding processes and may not accurately represent real scenes due to limitations in luminance range and contrast.
Innovation Solution
A method and apparatus for image processing that analyzes input images to determine the necessity of HDR functionality, sets an appropriate output mode, and generates an output image using a reference tone curve, allowing for optimized HDR image generation without complex encoding/decoding processes, by extracting key luminance values and adjusting tone curves based on image type, illuminance, and backlight luminance range.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex HDR encoding and decoding processes are used, then HDR image display capability is improved, but device complexity and processing time increase
Solution Approach 1:
The patent extracts only the essential HDR processing steps (luminance range analysis, tone curve generation, pixel value conversion) while eliminating complex encoding/decoding processes. This allows HDR image display with improved accuracy without proportionally increasing device complexity, as the solution focuses on extracting and implementing only the critical processing functions needed for HDR performance.
Solution Approach 2:
The patent performs preliminary analysis of the input image's luminance range and characteristics before processing. By pre-determining whether HDR processing is needed and pre-generating appropriate tone curves based on image analysis, the system avoids the need for complex real-time encoding/decoding operations, thereby improving HDR display capability while controlling processing complexity.
2Reliability
If HDR processing is applied to all images, then HDR image quality is improved, but processing time and energy consumption increase
Solution Approach 1:
The patent applies HDR processing selectively rather than universally. By analyzing image characteristics (luminance range, peak luminance values) and applying HDR processing only when the analysis indicates it is beneficial, the system improves image quality for appropriate images while avoiding unnecessary processing time and energy consumption for images that do not require HDR enhancement.
Solution Approach 2:
The patent performs preliminary image analysis to determine whether HDR processing is necessary before actually processing the image. This pre-assessment step allows the system to quickly identify images that benefit from HDR processing and skip complex processing for images that don't require it, thereby reducing overall processing time while maintaining high quality where needed.
3Measurement precision
If tone curve adjustment is performed based on multiple parameters, then image accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent segments the tone curve adjustment process into distinct, manageable steps: analyzing image luminance characteristics, determining processing mode (HDR or SDR), selecting or generating appropriate tone curves, and applying the conversion. This segmentation allows the system to achieve high luminance representation accuracy through multiple parameters while keeping each processing stage relatively simple and organized.
Solution Approach 2:
The patent changes key processing parameters (tone curve selection, processing mode) based on analyzed image characteristics such as luminance range and peak luminance values. By dynamically adjusting these parameters based on image content, the system achieves high measurement precision in luminance representation while avoiding the need for overly complex processing algorithms, as the parameter changes are based on straightforward image analysis.
Data Source
AI summary
A method of image processing includes extracting first image information from an input image by analyzing the input image, determining, based on the first image information, whether to utilize a high dynamic range (HDR) function for the input image, setting an image output mode based on a result of the determination, setting a reference tone curve for the input image based on the image output mode, and generating an output image by converting the input image based on the reference tone curve.