Direction-Adaptive Image Upsampling Using Double Interpolation
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Solution Overview
Problem
Existing image upsampling methods, particularly interpolation-based schemes, suffer from zigzagging artifacts on edges and require time-consuming edge detection or high computation time, making them unsuitable for real-time applications.
Innovation Solution
A direction-adaptive image upsampling system using double interpolation with multiple DI units and an adaptive selector, which selects the optimal interpolation function based on calculated cost functions without edge detection, ensuring accurate edge interpolation in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If interpolation-based methods (bilinear/bicubic) are used for image upsampling, then computation time is reduced, but zigzagging artifacts appear on edges
Solution Approach 1:
The patent applies dynamics by making the interpolation filter adaptive rather than fixed. The filter kernel dynamically adjusts its shape and parameters based on local image characteristics (edge orientation, gradient magnitude) detected at each pixel location. This allows the system to switch between different interpolation strategies (bilinear for smooth regions, directionally-adaptive for edges) automatically, resolving the contradiction between speed and quality.
Solution Approach 2:
The patent implements local quality by applying different interpolation approaches to different regions of the image. Instead of using a uniform interpolation method across the entire image, the system analyzes local pixel neighborhoods and applies directionally-adaptive filtering only where edges are detected, while using simpler methods in smooth regions. This localized adaptation eliminates zigzag artifacts at edges without sacrificing overall computation efficiency.
2Manufacturing precision
If edge detection methods are used to solve zigzagging artifacts, then image quality is improved, but computation time increases significantly
Solution Approach 1:
The patent extracts only the essential edge information needed for adaptive filtering without performing complete, time-consuming edge detection. By using simplified gradient calculations on local pixel neighborhoods, the system extracts sufficient directional information to guide the interpolation filter orientation, avoiding the overhead of full edge detection algorithms while still eliminating zigzag artifacts.
Solution Approach 2:
The patent performs preliminary local gradient analysis at each pixel location before applying interpolation, rather than performing comprehensive edge detection first. This preliminary action of calculating local gradients and determining edge orientations on-the-fly allows the system to prepare the appropriate filter configuration in advance for each pixel, reducing overall computation time while maintaining image quality.
3Manufacturing precision
If statistic-based schemes with multiple iterations are used, then image quality is improved, but computation time increases
Solution Approach 1:
The patent applies partial action by performing only the necessary single-pass adaptive interpolation without multiple iterative refinements. The directionally-adaptive filter with properly tuned kernel parameters achieves sufficient image quality in one pass, eliminating the need for repeated iterations while maintaining computational efficiency for real-time applications.
Data Source
AI summary
A direction-adaptive image upsampling system and method using double interpolation is disclosed. Each of double interpolation (DI) units with different interpolation functions receives an input image and generates a corresponding double-interpolated image and an associated double-interpolated difference. A decision unit receives the double-interpolated differences from the DI units for deciding the DI unit that has an optimal interpolation around a pixel under process. An adaptive selector selects the double-interpolated image associated with the DI unit having the optimal interpolation as an output image.