Color Interpolation Using Edge Detection to Reduce Image Blurring
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Solution Overview
Problem
Existing demosaicing techniques for color image sensors often result in visible artifacts and a loss of image sharpness due to inadequate interpolation methods that fail to account for image edges, leading to blurring and decreased sharpness.
Innovation Solution
A method for color plane interpolation that differentiates interpolation based on edge direction and pixel location within an image, using a five by five kernel to calculate and adjust interpolation values, particularly for green, red, and blue pixels, to reduce blurring and enhance edge detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional demosaicing interpolation is used to reconstruct missing color values, then color image can be generated from single-color pixel data, but image sharpness is lost and artifacts appear due to inadequate handling of edge regions
Solution Approach 1:
The patent applies different interpolation strategies to different regions of the image based on edge detection results. For pixels near detected edges, a different interpolation formula is used compared to pixels in uniform regions. This local differentiation preserves edge sharpness while maintaining color accuracy in both regions.
Solution Approach 2:
The patent performs edge detection and classification before performing the actual color interpolation. By pre-identifying edge regions and assigning appropriate interpolation weights beforehand, the method avoids post-processing artifacts and ensures sharpness is maintained from the outset.
2Productivity
If simple interpolation methods are used to calculate missing color values, then processing speed is maintained, but visible artifacts such as zipper effects and random color dots appear
Solution Approach 1:
The patent dynamically adjusts interpolation parameters (weights for different neighboring pixels) based on local image characteristics detected through edge analysis. By changing these parameters adaptively rather than using fixed simple interpolation, the method eliminates artifacts like zipper effects while maintaining computational efficiency.
3Device complexity
If uniform interpolation is applied to all pixels, then processing complexity is minimized, but edge regions suffer from blurring and loss of detail
Solution Approach 1:
The patent implements local quality by detecting edges and applying different interpolation formulas specifically to pixels adjacent to detected edges. This targeted approach improves edge sharpness without requiring complete redesign of the interpolation process for the entire image.
Solution Approach 2:
The patent segments the image into edge regions and non-edge regions through edge detection, then applies appropriate interpolation methods to each segment. This segmentation allows complex edge-preserving interpolation only where needed, maintaining overall processing efficiency.
Data Source
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AI summary
A method and apparatus for color plane interpolation are provided which interpolates the color values of pixels differently depending on an edge direction and whether a pixel is at an edge within an image. The use of the edge detection during the interpolation of each of the colors present in the color pattern helps reduce some of the disadvantages of the loss of image sharpness abundant in known demosaicing techniques.