Adaptive Image Filtering Coefficient Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current image-filtering technologies, such as median filters, are inefficient in enhancing image characteristics, particularly under smooth edges and fail to anticipate changes in high-frequency signals, leading to unclear output images.
Innovation Solution
An image-filtering method and device that calculates optimal filtering coefficients by determining a difference function between target and desired output pixel values using characteristic filtering coefficients, minimizing the difference through a linear equation, and applying these coefficients to each pixel for enhanced filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If median filters are used for false color reduction, then incorrect colors on sharp edges are removed efficiently, but the efficiency decreases under smooth edges and high frequency signal changes cannot be anticipated
Solution Approach 1:
The patent applies dynamics by making the filtering coefficients adaptive rather than fixed. The optimal filtering coefficients are calculated based on the actual image characteristics (gradient magnitude, variance) of each processing region, allowing the filter to dynamically adjust its behavior. This resolves the contradiction by enabling the filter to perform well on both sharp edges (where median filters excel) and smooth edges (where traditional filters fail), as the coefficients are optimized for each specific local condition.
2Device complexity
If traditional filtering methods are used, then processing is simple, but the clarity of the output image cannot be guaranteed under varying conditions
Solution Approach 1:
The patent applies preliminary action by pre-calculating the optimal filtering coefficients based on the image characteristics before the actual filtering operation. The system analyzes the input image to determine gradient magnitudes, variances, and other characteristics, then uses these to calculate the optimal coefficients in advance. This preliminary analysis ensures that when the filtering is applied, the output image clarity is optimized for the specific content being processed, resolving the contradiction between simplicity and precision.
3Productivity
If fixed filtering coefficients are used, then the filtering process is efficient, but the filter cannot adapt to different image characteristics and conditions
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the filtering coefficients based on image characteristics. Instead of using fixed coefficients, the system calculates optimal coefficients by changing parameters such as gradient magnitude thresholds, variance values, and weighting factors according to the local image content. This allows the filter to maintain high processing efficiency while adapting to different image characteristics, resolving the contradiction between productivity and adaptability.
Data Source
AI summary
An image-filtering method that includes the steps outlined below is provided. Target image values and an input image having input pixel values are retrieved. A difference function between filtering response values of a desired output image and the target image values is determined, wherein the filtering response values are generated by filtering desired output pixel values of the desired output image based on characteristic filtering coefficients. An optimal solution of a desired output central pixel value of the desired output image is calculated according to a linear equation related to the characteristic filtering coefficients, wherein the optimal solution minimizes a value of the difference function. A corresponding relation between the desired output central pixel values and the input pixel values are retrieved from the optimal solution to calculate optimal filtering coefficients. A filtering circuit performs filtering on each pixel of an image under processing according to the optimal filtering coefficients.