Simulating Image Boundary Sharpness Using Contrast Sensitivity Function
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Solution Overview
Problem
Display devices face challenges in optimizing pixel arrangement structures and rendering methods to achieve high sharpness, as these factors are difficult to change post-manufacturing, and existing methods lack efficient simulation techniques to derive optimal design values.
Innovation Solution
A method and apparatus that simulate image boundary sharpness by setting a boundary pattern with a unit pattern, calculating simulation grayscale data, and obtaining a sharpness index using a contrast sensitivity function and brightness data, while considering human visual perception characteristics and pixel arrangement structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixel arrangement structure and rendering method are optimized to improve sharpness, then image quality is improved, but device complexity and manufacturing difficulty increase
Solution Approach 1:
The patent applies preliminary action by performing sharpness simulation and evaluation during the design phase before manufacturing. The system calculates simulation grayscale data based on candidate pixel arrangement structures and rendering methods, then evaluates sharpness using CSF and brightness data. This allows optimal designs to be selected in advance, avoiding the need to change complex pixel structures after manufacturing.
2Measurement precision
If pixel arrangement structure is changed to improve sharpness, then image quality is improved, but manufacturing cost and time increase
Solution Approach 1:
The system performs sharpness evaluation during the design phase using simulation grayscale data and CSF-based metrics. By determining optimal pixel arrangement structures and rendering methods before manufacturing, the patent avoids costly post-manufacturing changes and enables selection of designs that balance sharpness with manufacturing feasibility.
3Measurement precision
If rendering method is optimized to improve sharpness, then image quality is improved, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by evaluating multiple rendering methods through sharpness simulation during the design phase. The system calculates simulation grayscale data for each rendering method using the same pixel arrangement structure, then compares sharpness metrics to identify the optimal rendering approach. This preliminary evaluation avoids the need for complex real-time adjustments during operation.
4Speed
If sharpness simulation is performed without considering human visual perception, then calculation speed is improved, but measurement precision deteriorates
Solution Approach 1:
The patent applies parameter changes by incorporating human visual perception characteristics through the contrast sensitivity function (CSF) into the sharpness evaluation. The system frequency converts brightness data, multiplies it by the CSF filter to weight different spatial frequencies according to human sensitivity, and then performs inverse frequency conversion. This transforms the evaluation parameters to match human perception, improving accuracy without requiring excessively complex calculations.
Data Source
AI summary
A method for simulating sharpness of an image boundary including setting a boundary pattern including a boundary line between black and white, and a unit pattern including arrangement information of pixels; calculating simulation grayscale data for implementing the boundary pattern by using the unit pattern; and obtaining a sharpness index for the boundary line based on a contrast sensitivity function (CSF) and brightness data extracted from the simulation grayscale data.