Imaging Pixel Interpolation Using RGBW12 Correlation
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Solution Overview
Problem
Existing image pickup elements face challenges in interpolation precision due to the use of pixel data from far or different colored pixels, leading to reduced image resolution and increased false color occurrence.
Innovation Solution
The implementation of an RGBW12 pattern in the image pickup element, where white pixels have a wider spectral response and are arranged to surround color pixels, allowing for higher correlation value calculations in multiple directions to improve interpolation precision and reduce false color.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If interpolation processing uses pixel data from far or different colored pixels, then more pixels can be utilized for interpolation, but interpolation precision decreases and false color increases
Solution Approach 1:
The patent applies local quality by using only adjacent pixels of the same color for interpolation, ensuring that the local neighborhood provides the most relevant and accurate data. This prevents using distant or different-colored pixels that would degrade interpolation precision while still utilizing sufficient neighboring pixels for the process.
Solution Approach 2:
The patent changes the parameter of pixel selection criteria by introducing correlation value calculations in multiple directions (horizontal, vertical, diagonal). This allows the system to dynamically select the best direction for interpolation based on actual pixel correlations, improving precision without requiring distant pixels.
2Reliability
If white pixels with wider spectral response are used, then sensitivity and signal-to-noise ratio improve, but color accuracy may be compromised without proper interpolation
Solution Approach 1:
The patent uses adjacent pixels of the same color as intermediaries to transfer color information to white pixels. By calculating correlation values and selecting the best direction for interpolation, the system accurately reconstructs color data from neighboring same-colored pixels, preventing color accuracy degradation while maintaining the high sensitivity benefits of white pixels.
Solution Approach 2:
The patent makes white pixels multi-functional by enabling them to serve both as high-sensitivity luminance sensors and as locations for precise color interpolation. The dual approach of using white pixels for S/N ratio improvement while applying sophisticated interpolation for color accuracy recovery allows the system to leverage all pixel types effectively.
3Measurement precision
If correlation calculation considers multiple directions, then interpolation accuracy improves, but processing complexity increases
Solution Approach 1:
The patent applies partial action by calculating correlations in only the most necessary directions (horizontal, vertical, and two diagonals) rather than all possible directions. This selective approach provides sufficient interpolation accuracy while avoiding excessive computational complexity that would arise from considering every possible pixel relationship.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances interpolation precision, increases image resolution, and reduces false color by utilizing the higher sensitivity and wider spectral response of white pixels, resulting in improved image quality with higher spatial frequency resolution.
Implementation Method 1
each pixel having a photoelectric converting unit, wherein a wavelength band range of light to be photoelectrically converted by the photoelectric converting unit of the first pixel is a first wavelength band range
Data Source
AI summary
A plurality of adjacent pixels is provided adjacently in a plurality of directions to a first pixel. A direction with a highest correlation is derived from signals of the plurality of pixels, and the direction with the highest correlation is reflected to interpolation processing to be performed on the signal of first pixel.