RGBW Image Sensor Demosaic Processing for False Color Reduction
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Solution Overview
Problem
The miniaturization of image sensors with RGBW patterns leads to reduced light incidence and S/N ratio, resulting in false colors and decreased resolution due to chromatic aberration, especially near edges, and increased costs from additional optical lenses to mitigate these issues.
Innovation Solution
An image processing apparatus with a data transform processing unit that performs pixel transformation by analyzing two-dimensional pixel arrays, utilizing edge detection, texture analysis, and parameter calculation to adjust blend ratios for accurate color interpolation, effectively reducing false colors and improving resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If an RGBW pattern is used to increase light transmission and sensitivity, then higher sensitivity is achieved, but false colors and resolution degradation occur due to reduced sampling rates for R, G, and B components
Solution Approach 1:
The patent introduces an image processing apparatus as an intermediary between the RGBW image pickup element and the final color image output. This intermediary performs sophisticated demosaic processing that uses the W pixel data to reconstruct R, G, and B components, thereby maintaining the high light transmission advantage of RGBW while compensating for the color accuracy losses through computational methods.
Solution Approach 2:
The patent changes the processing parameters by using multiple different demosaic processing methods with different characteristics and selectively combining their results. By adjusting the blend ratio between different processing methods based on local image characteristics (such as edge presence), the system optimizes both color accuracy and light transmission utilization.
2Ease of operation
If demosaic processing is performed on RGBW data, then color images can be generated, but false colors are generated due to decreased sampling rates for R, G, and B components
Solution Approach 1:
The patent employs dynamic processing by detecting edges in the image and adaptively changing the demosaic processing strategy based on local characteristics. In edge regions where false colors are more problematic, the system adjusts the blend ratio to favor methods that preserve edge sharpness and reduce color artifacts, while in non-edge regions it uses methods optimized for color accuracy.
Solution Approach 2:
The system incorporates feedback mechanisms by evaluating the results of different demosaic processing methods and using this information to adjust the blend ratio. The edge detection results and local image characteristics provide feedback that guides the selection and weighting of different processing approaches, thereby reducing false colors while maintaining color image generation capability.
3Quantity of substance
If optical lenses with large chromatic aberration are used, then more light can be collected, but light collecting rates for RGB wavelength components drop and resolution decreases
Solution Approach 1:
The patent replaces the mechanical/optical solution (using multiple lenses with different refractive indices to correct chromatic aberration) with a computational approach. Instead of modifying the optical system, the image processing apparatus uses software-based demosaic processing to compensate for the resolution losses caused by chromatic aberration, thereby maintaining light collection efficiency while preserving image quality.
4Manufacturing precision
If the number of optical lenses is increased to suppress chromatic aberration, then chromatic aberration is reduced, but costs are increased
Solution Approach 1:
The patent substitutes the mechanical approach of adding more optical lenses with a computational image processing approach. The image processing apparatus performs sophisticated demosaic processing that compensates for chromatic aberration effects in software, thereby achieving chromatic aberration suppression without increasing the number of physical lenses or system cost.
Data Source
AI summary
To provide an apparatus that generates an RGB pattern data from an image pickup signal by an image pickup element having an RGBW pattern and a method. An edge detection unit analyzes an output signal of the image pickup signal of the RGBW pattern to obtain edge information corresponding to the respective pixels, and a texture detection unit generates texture information. Furthermore, a parameter calculation unit executes an interpolation processing in which an applied pixel position is changed in accordance with an edge direction of a transform target pixel to generate parameters equivalent to an interpolation pixel value. In a blend processing unit, the parameters generated by the parameter calculation unit, the edge information, and the texture information are input, in accordance with the edge information and the texture information corresponding to the transform pixel, a blend ratio of the parameters calculated by the parameter calculation unit is changed, the blend processing is executed, and a transform pixel value is decided.