Display Image Transform Using Dual Alpha Beta Parameters
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for enhancing digital image appearance on electronic displays in ambient light fail to provide optimal visual experience due to distortion from screen reflections and varying content types, requiring a method that adapts to both display conditions and image characteristics without specific analysis.
Innovation Solution
The method involves calibrating an image transform process based on display properties and further modifying it according to the type or quality of content being displayed, using a two-part parameter system where alpha is tuned for display properties and beta is tuned for content-specific adjustments, allowing for optimal image enhancement regardless of content type.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single strength parameter is used for image transformation, then the implementation is simple, but the image quality is poor and not optimal for different content types
Solution Approach 1:
The patent segments the single strength parameter into two independent parameters: alpha (for display properties) and beta (for content characteristics). This segmentation allows each parameter to be optimized independently for its specific purpose, resolving the contradiction between simplicity and image quality by making the system adaptable to different content types while maintaining a manageable two-parameter structure.
Solution Approach 2:
The patent introduces dynamic adaptability by making the image transformation process responsive to both display conditions (via alpha) and content characteristics (via beta). This dynamic parameter adjustment enables the system to optimize image quality for varying content types without requiring complete system redesign, balancing complexity and performance.
2Illumination intensity
If the strength parameter is increased to compensate for ambient light, then dark areas become more visible, but compression artifacts are revealed and image quality deteriorates
Solution Approach 1:
The patent applies local quality by using the beta parameter to selectively adjust transformation strength based on content characteristics. Different content types (photographs, videos, graphics) receive different beta values, allowing dark areas to be enhanced appropriately for each content type without uniformly revealing compression artifacts across all content.
Solution Approach 2:
The patent changes the transformation parameter (strength) based on content characteristics through the beta parameter. By adjusting beta according to content type, the system optimizes the balance between dark area visibility and artifact suppression, applying stronger transformation only when appropriate for the specific content being displayed.
3Manufacturing precision
If content-specific parameters are introduced to optimize image quality, then image quality improves, but the system complexity increases
Solution Approach 1:
The patent achieves universality by creating a content-characteristic-based parameter system that works across multiple content types (photographs, videos, graphics, games). The beta parameter serves as a universal mechanism to adapt the image transformation to any content type without requiring content-specific algorithms for each format, thus improving image quality while controlling system complexity.
Data Source
AI summary
In a method of enhancing the appearance of a digital image on an electronic display, Ambient Light Sensor (ALS) and Screen Brightness (SB) inputs are combined with a calibration input 12 to generate a first strength parameter 22, including an alpha component that is dependent only upon the properties of the display. Then a further, content-based input 24 is also combined to generate a second strength parameter 26, including a beta component that is dependent only upon a content type, or a content quality, or both.