Pixel Interpolation via Dynamic Edge Detection Ranges
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Solution Overview
Problem
Existing pixel interpolation methods fail to effectively improve interpolated image quality due to inadequate edge detection and direction selection, leading to suboptimal results in deinterlacing and image-scaling operations.
Innovation Solution
A pixel interpolation method and device that dynamically sets edge detection ranges based on image features by determining pixel values of reference pixels, performing edge detection to select an appropriate edge direction for each target position, and interpolating pixel values accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed edge detection range is used for all target positions, then the device complexity is reduced and processing speed is improved, but the measurement precision of edge detection deteriorates and interpolated image quality worsens
Solution Approach 1:
The patent applies dynamics by making the edge detection range adaptive rather than fixed. The control unit dynamically adjusts the edge detection range for each target position based on image content characteristics, allowing the system to optimize detection precision for different regions while maintaining manageable processing complexity through automated adaptation.
Solution Approach 2:
The patent implements local quality by applying different edge detection ranges to different target positions within the image. Instead of using a uniform approach, the system tailors the detection range to local image characteristics, improving overall detection precision by adapting to varying edge densities and orientations in different regions.
2Manufacturing precision
If a fixed edge detection range is used for all target positions, then the processing speed is improved, but the interpolated image quality deteriorates
Solution Approach 1:
The system dynamically adjusts the edge detection range based on local image characteristics, optimizing interpolation precision for each target position. The control unit automatically adapts the detection parameters, achieving high interpolation quality without requiring manual intervention to balance speed and precision.
Solution Approach 2:
The system performs self-service by automatically selecting appropriate edge detection ranges for each target position based on image content analysis. The control unit independently determines optimal parameters without external intervention, enabling the system to maintain high interpolation precision while processing efficiency is preserved through automated decision-making.
3Reliability
If edge detection is performed without dynamic range adjustment, then the ease of operation is improved, but the reliability of edge detection deteriorates
Solution Approach 1:
The system achieves self-service by automatically performing edge detection with dynamically adjusted ranges for each target position. The control unit independently analyzes image characteristics and selects appropriate detection parameters, eliminating the need for manual configuration while ensuring reliable edge detection across diverse image regions.
Solution Approach 2:
The system implements feedback by using the results of image content analysis to adjust edge detection ranges. The control unit continuously adapts detection parameters based on detected image features, creating a closed-loop system that improves detection reliability while maintaining operational simplicity through automated feedback-driven adjustment.
Data Source
AI summary
A pixel interpolation method for interpolating pixel values of a plurality of target positions of a target picture is disclosed. The pixel interpolation method includes: dynamically setting a plurality of edge detection ranges corresponding to the plurality of target positions, respectively; and for each of the plurality of target positions, performing a edge detection according to a corresponding edge detection range to determine an edge direction for the target position, and interpolating a pixel value for the target position according to pixel data corresponding to the edge direction.