Bayer-to-RGB Edge Pixel Adjustment for False-Color Reduction
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Solution Overview
Problem
The conversion of Bayer images to RGB format often results in conversion deviations leading to false colors due to interpolation algorithms and spatial undersampling, particularly at image edges.
Innovation Solution
A color adjustment method that determines an adjustment area around edge pixels, acquires color information of similar pixels, and adjusts the parameter values of edge pixels based on the color information and brightness parameters to align with actual values, thereby reducing false colors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If linear neighborhood interpolation is used to convert Bayer image to RGB format, then the conversion process can be completed, but conversion deviation occurs leading to false color at edge pixels
Solution Approach 1:
The patent applies local quality by treating edge pixels differently from interior pixels. Edge pixels are identified through gradient calculation, and then different interpolation methods are applied: bilinear interpolation for interior pixels and constrained interpolation using adjustment areas for edge pixels. This localized differentiation resolves the contradiction by improving color accuracy at edges without compromising the overall conversion efficiency.
Solution Approach 2:
The patent segments the image into different regions based on pixel type (edge vs. interior). By calculating gradients and identifying edge pixels, the system divides the image into adjustment areas containing edge pixels and regular areas containing interior pixels. This segmentation allows applying appropriate interpolation methods to each region, resolving the contradiction between conversion completeness and color accuracy.
2Adaptability or versatility
If interpolation algorithm is applied to obtain color component values, then the Bayer image can be converted to RGB format, but spatial undersampling causes conversion deviation and false color
Solution Approach 1:
The patent changes the interpolation parameters based on pixel location. For edge pixels, the system uses constrained interpolation parameters that incorporate adjustment area information and gradient-based weighting, while interior pixels use standard bilinear interpolation parameters. This parameter adaptation resolves the contradiction by maintaining versatility in format conversion while improving color accuracy through location-aware parameter selection.
Solution Approach 2:
The patent implements feedback through gradient calculation and edge detection. The system calculates gradients to identify edge pixels, then uses this feedback information to select appropriate interpolation methods. The adjustment areas are determined based on edge pixel locations, creating a feedback loop that continuously refines the interpolation process. This feedback mechanism resolves the contradiction by adapting the conversion process to actual image content.
Data Source
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AI summary
Provided are a color adjustment method, a color adjustment device, an electronic device, and a computer-readable storage medium. The method includes: determining an adjustment area corresponding to an edge pixel, where the adjustment area includes multiple pixels; acquiring color information of the edge pixel and color information of each similar pixel in the adjustment area, where a pixel type of the similar pixel is consistent with a pixel type of the edge pixel; and adjusting a parameter value of the edge pixel according to the color information of the each similar pixel, the color information of the edge pixel, and a brightness parameter of the edge pixel.