Adaptive Edge Enhancement for Display Devices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current display devices face challenges in optimizing edge enhancement for images of varying quality, such as standard definition (SD) and high definition (HD), leading to blurred edges when up-converting SD images to HD, as existing methods fail to set the optimal enhancement degree based on the image's characteristics.
Innovation Solution
An edge adjustment method that extracts edge components, calculates their sum, and determines the enhancement degree based on the sum, average luminance, proportion of high luminance regions, and distribution of luminance components to adjust the edge enhancement accordingly, ensuring the edge is enhanced suitably for the image's characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If edge enhancement is applied to up-converted SD images to improve edge clarity, then edge sharpness is improved, but over-enhancement occurs on HD images causing quality degradation
Solution Approach 1:
The patent changes the enhancement degree parameter dynamically based on image characteristics. It calculates the sum of edge components for the input image and determines the enhancement degree accordingly - using a first enhancement degree for images with smaller edge component sums (up-converted SD images) and a second enhancement degree for images with larger edge component sums (HD images), preventing over-enhancement while ensuring sufficient edge sharpness
Solution Approach 2:
The patent implements dynamic adjustment of the enhancement degree based on real-time analysis of image characteristics. The system automatically adapts the enhancement parameter by evaluating edge component sums and selecting appropriate enhancement degrees, making the edge enhancement process flexible and adaptive rather than fixed
2Device complexity
If a fixed enhancement degree is used for all images to simplify processing, then device complexity is reduced, but edge enhancement becomes unsuitable for different image characteristics
Solution Approach 1:
The patent enables the system to automatically determine the appropriate enhancement degree by itself based on image characteristics. The device calculates edge component sums and autonomously selects enhancement degrees without requiring external input or complex manual configuration, achieving self-adaptive edge enhancement
Solution Approach 2:
The patent changes the enhancement degree parameter based on calculated edge component sums. By analyzing image characteristics and dynamically adjusting the enhancement parameter, the system achieves high adaptability without requiring complex device architecture
3Speed
If maximum luminance difference is used to estimate maximum frequency for edge enhancement, then processing speed is improved, but measurement precision of edge characteristics deteriorates
Solution Approach 1:
The patent extracts edge components from the input image and calculates their sums to directly represent edge characteristics. This extraction approach provides more accurate measurement of edge frequency and density compared to using maximum luminance difference, enabling precise determination of enhancement degree
Solution Approach 2:
The patent replaces the mechanical estimation method (using maximum luminance difference to infer maximum frequency) with a more accurate approach based on actual edge component analysis. This substitution improves measurement precision while maintaining processing efficiency through direct edge component summation
Data Source
Figure 1
Figure 2
Figure 3(a)~3(c)
AI summary
It is an object to provide an edge adjustment method for performing adjustment such as edge enhancement suited to the characteristics of an input image, an image processing device for performing edge adjustment by using such method, and a display apparatus for displaying the image performed with the edge adjustment. A noise removing filter 21 removes noise from an input image and an edge component extracting unit 23 extracts edge components. The edge components are extracted by calculating a difference between the input image and a smoothed image, which is obtained by smoothing the input image in a smoothed image generating portion 24. An edge component comparing unit 26 compares the extracted edge components with a threshold value and a sum calculating unit 27 calculates the sum of the edge components greater than the threshold value. A control circuit 11 determines the enhancement degree of the edges based on the sum and averaged luminance of the input image calculated by an average luminance calculating unit 22. An enhancement degree adjustment unit 28 adjusts the determined enhancement degree, and an edge component enhancement unit 30 enhances the edge components based on this enhancement degree and adds it to the input image to perform edge enhancement processing.