Directional Image Interpolation Using Gradient Confidence
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Solution Overview
Problem
Conventional image interpolation technologies often result in sawtooth or blurred edges when increasing image resolution, and advanced methods require high hardware and computing costs, making real-time processing difficult.
Innovation Solution
An image processing apparatus that includes a gradient calculation unit, direction determining unit, directional interpolation unit, image interpolation unit, and blender unit, which performs directional interpolation based on edge directions and confidence values to enhance image sharpness while maintaining low operational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional image interpolation technology is used, then hardware cost and computing resource requirement are low, but sawtooth appearance or blurring occurs at image edges
Solution Approach 1:
The patent divides the image processing into multiple stages: gradient calculation, direction determination, and directional interpolation. By segmenting the interpolation process into direction-aware steps, the patent achieves edge-preserving quality improvement without requiring complex covariance-based methods, thus resolving the contradiction between image quality and hardware complexity
Solution Approach 2:
The patent applies different interpolation strategies based on local image characteristics by calculating gradient directions at each pixel location. Edge regions receive directional interpolation treatment while non-edge regions use standard interpolation, achieving high quality results with moderate computational requirements
2Manufacturing precision
If advanced interpolation process based on covariance is used, then image quality is improved, but hardware and computing costs increase making real-time processing difficult
Solution Approach 1:
The patent extracts only the essential directional information (gradient magnitude and angle) from the image data, discarding the computationally intensive covariance calculations. This extraction of key features maintains image quality improvement while dramatically reducing computing costs and enabling real-time processing
Solution Approach 2:
The patent uses simple gradient-based directional information as a substitute for expensive covariance-based interpolation. This cheaper approximation method achieves sufficient image quality without the high computational burden, making real-time processing feasible
Data Source
AI summary
An image processing apparatus includes a gradient calculation unit, a direction determining unit, a directional interpolation unit, and a blender unit. The gradient calculation unit processes an input image to generate gradient magnitudes and gradient angles associated with input pixels of the input image. The direction determining unit generates interpolation angles and directional confidence values according to the gradient magnitudes and gradient angles. The directional interpolation unit performs directional interpolation on the input image according to the interpolation angles, so as to generate a first image with an image resolution different from the input image. The blender receives the first image and a second image generated from interpolating the input image, and blends the first image and the second image according to the directional confidence values to generate an output image.