Image Interpolation Using Edge-Direction Low Pass Filtering
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Solution Overview
Problem
Conventional image interpolation methods, such as nearest neighbor and bilinear interpolation, often result in image blurring or blocking effects when dealing with images of standard definition resolution displayed on high-resolution flat panel displays, particularly when the image resolution does not match the display resolution, leading to poor picture quality.
Innovation Solution
An apparatus and method for image interpolation based on low pass filtering, which involves detecting the edge direction of a pixel nearest to the to-be-interpolated pixel, calculating pixel values using adjacent pixels within a lattice filtering window, and applying low pass filtering according to the determined edge direction to smooth out uneven edges and prevent image deterioration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If nearest neighbor interpolation is used, then processing speed is high, but image quality deteriorates with staircase phenomenon and errors
Solution Approach 1:
The patent changes the interpolation parameter from simple pixel value copying to using gradient calculation and edge direction detection. By computing gradients in horizontal and vertical directions and determining edge directions, the method adapts the interpolation process to local image characteristics, thereby improving image quality while maintaining reasonable processing speed through directional awareness.
Solution Approach 2:
The patent applies different interpolation strategies based on local edge directions detected in different regions of the image. By identifying horizontal edges, vertical edges, and other directions locally, the method tailors the pixel value calculation to each region's specific characteristics, preventing staircase effects at edges while maintaining smooth transitions in uniform areas.
2Manufacturing precision
If bilinear interpolation is used, then image quality improves with reduced error, but processing complexity increases and blocking effects occur
Solution Approach 1:
The patent modifies the weight calculation parameters in bilinear interpolation by incorporating gradient information and edge direction detection. Instead of using uniform distance-based weights, the method adjusts weights based on detected edge directions, allowing for more accurate pixel value allocation at edges while reducing blocking effects through directional awareness in the weighting scheme.
3Productivity
If standard bilinear interpolation is used, then pixel values are calculated efficiently, but blocking effects are generated due to independent pixel allocation
Solution Approach 1:
The patent applies edge direction detection and gradient calculation locally at each pixel position to determine appropriate weighting factors. By identifying whether a pixel lies near horizontal edges, vertical edges, or other directional transitions, the method adjusts the interpolation weights locally, preventing blocking effects at edges while maintaining calculation efficiency through the use of simple gradient-based directional classification.
Data Source
AI summary
An apparatus and method for image interpolation based on low pass filtering are provided. The apparatus includes an edge direction detector detecting an edge direction for a pixel nearest to a to-be-interpolated pixel among pixels and determining the edge direction of the to-be-interpolated pixel as the detected edge direction, a pixel value calculator calculating pixel values of interpolation points located in a lattice filtering window having a predetermined size by using pixel values of pixels located adjacent to the interpolation points, and a filtering unit performing low pass filtering on the to-be-located pixel according to a low pass filter corresponding to the determined edge direction of the to-be-interpolated pixel, the low pass filter being one of low pass filters corresponding to predetermined vertical, horizontal, left diagonal and right diagonal directions respectively. Accordingly, a process of calculating the pixel value of the to-be-interpolated pixel can be simplified and a processing speed can be increased. Furthermore, it is possible to obtain a high-quality image without having image deterioration such as blocking effect caused by an error in a pixel value even for a region with an uneven edge.