Adaptive Image Quality Enhancement via Iterative Filter Parameter Updates
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current image quality enhancement solutions for display devices require continuous adjustment of parameters based on different image types and contents, leading to inferior enhancement when using fixed parameters across varying images.
Innovation Solution
A display device system and method that adaptively enhance image quality by utilizing iterative detail enhancement processing with filter functions having iteratively-updated parameters, based on edge features and high-frequency information of input images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed parameters are used for image quality enhancement, then the processing is simple and fast, but the enhancement quality is inferior for different image types
Solution Approach 1:
The patent implements dynamic parameter adjustment by iteratively updating filter parameters based on quality evaluation scores. The system transitions from static fixed parameters to dynamic adaptive parameters that change during the enhancement process, allowing the same processing framework to adapt to different image types while maintaining efficient processing through automated iteration.
Solution Approach 2:
The patent changes filter parameters iteratively based on quality evaluation. Different parameters (such as sharpness, contrast, saturation) are adjusted in each iteration according to the evaluated quality score, enabling the system to optimize enhancement quality for different image types without manual intervention.
2Manufacturing precision
If parameters are continuously adjusted for different image types, then the enhancement quality is improved, but the processing complexity increases
Solution Approach 1:
The patent implements self-service through automated quality evaluation and parameter adjustment. The system automatically evaluates the quality of enhanced images and adjusts parameters without user intervention, reducing processing complexity from the user perspective while maintaining high enhancement quality through iterative optimization.
Solution Approach 2:
The patent uses feedback loops where the quality evaluation score of each enhanced image feeds back into the parameter adjustment process. This closed-loop system automatically refines parameters based on actual enhancement results, improving quality while managing complexity through algorithmic automation rather than manual control.
3Manufacturing precision
If iterative detail enhancement processing is performed, then the image quality is maximized, but the processing time increases
Solution Approach 1:
The patent applies periodic action through iterative processing cycles. Instead of continuous processing, the system performs enhancement in discrete iterations with quality evaluation at each step, allowing the process to be interrupted or adjusted while maintaining quality improvement through structured periodic refinement.
Data Source
AI summary
Disclosed are a display device system and a method for adaptively enhancing an image quality. The method includes: acquiring an original image, performing iterative detail enhancement processing on the original image by utilizing at least one filter function containing iteratively-updated filter parameters, in a case that a difference between a quality evaluation score of the input image and a quality evaluation score of the detail-enhanced image of the ith iteration satisfies an iteration condition, obtaining filter parameters of an (i+1)th iteration by updating the filter parameters of the ith iteration, and continuing to perform detail enhancement processing on the input image by utilizing at least one filter function containing the filter parameters of the (i+1)th iteration, until a difference between the quality evaluation score of the input image and a quality evaluation score of a detail-enhanced image of the (i+1)th iteration satisfies the iteration condition.