Image Quality Adjustment Using Bézier Curve Mapping
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Solution Overview
Problem
Existing HDR imaging technologies fail to adjust images intelligently according to different environments or user preferences, resulting in unsatisfactory visual experiences.
Innovation Solution
A method that uses artificial intelligence to select a focus area of interest within an image, applies a fifth-order linear Bézier curve to adjust luminance values, and scales edge coefficients to enhance image quality, allowing for real-time contrast and luminance adjustments without requiring additional hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing HDR technologies adjust images mechanically, then the adjustment process is simple and fast, but the image quality enhancement is not intelligent and does not meet user-specific demands
Solution Approach 1:
The system automatically identifies focus areas and adjusts luminance values without requiring manual user input. The display device system autonomously performs image quality enhancement by selecting focus areas and applying luminance adjustments based on predefined algorithms, making the system self-sufficient in delivering intelligent image processing.
Solution Approach 2:
The patent adjusts the luminance value parameter of pixels within the identified focus area to enhance image quality. By changing the luminance parameter selectively in different regions (increasing in focus areas, maintaining or decreasing in non-focus areas), the system achieves intelligent image enhancement without uniformly processing the entire image, thus balancing intelligence with computational efficiency.
2Illumination intensity
If luminance values are increased across the entire image, then the image becomes brighter overall, but the contrast and visual impact in specific areas of interest are reduced
Solution Approach 1:
The patent applies different luminance adjustment strategies to different regions of the image. Focus areas receive increased luminance values to enhance brightness and visual impact, while non-focus areas maintain or reduce their luminance values. This localized quality enhancement ensures that specific areas of interest stand out with improved contrast and visual impact, while the overall image maintains appropriate brightness levels.
3Manufacturing precision
If advanced AI processing is implemented for focus area selection, then image quality enhancement becomes more intelligent and personalized, but the processing time and computational resources increase
Solution Approach 1:
The system pre-identifies focus areas using efficient algorithms that can quickly analyze image content and determine regions of interest. By performing focus area selection in advance and using predefined adjustment strategies, the system reduces real-time processing requirements while maintaining high image quality enhancement precision. The luminance value adjustments are applied based on pre-determined focus areas, minimizing computational overhead during actual image processing.
Data Source
AI summary
The disclosure provides a method, device, and readable storage medium for adjusting image quality. The display device system selects a focus area of a target image, and outputs a mapping relationship curve of an input luminance value and an output luminance value of the target image. Then, an input luminance value range of pixels in the focus area of the target image is calculated, and upper and lower edge coefficients of the input luminance value range are proportionally adjusted to obtain new upper and lower edge coefficients. The mapping relationship curve is adjusted according to the new upper and lower edge coefficients, thereby adjusting the focus area of the target image.