Low Light Color Imaging via Periodic RGB Illumination
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Solution Overview
Problem
Current color imaging in low light environments faces challenges such as noise, motion blur, and resolution degradation due to inefficient light detection by Bayer filters and external illuminators, which are not adaptive to scene requirements and consume excessive power.
Innovation Solution
A system and method that involves illuminating red, green, and blue lights at different time periods, capturing separate frames, generating intermediate color frames, determining true colors for moving pixels, and adaptively adjusting illumination to enhance image quality, eliminating the need for Bayer filters and reducing noise and motion artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If exposure time is increased to collect more photons, then noise is reduced, but motion blur increases due to object motion within the exposure period
Solution Approach 1:
The patent uses periodic illumination with red, green, and blue lights at different time periods to capture separate color frames. This periodic action allows the system to collect sufficient photons for each color channel without requiring long continuous exposure, thereby reducing motion blur while maintaining acceptable noise levels through multiple short exposures combined with image processing.
2Ease of operation
If Bayer filter is used for color detection, then color images can be captured, but light detection efficiency decreases to about 20% and color signal crosstalk increases
Solution Approach 1:
The patent removes the Bayer filter from the optical path entirely. Instead of using a color filter array that blocks most light, the system captures monochrome frames with the full sensor array and then assigns color information through computational processing based on periodic illumination. This extraction of the Bayer filter eliminates the 80% light loss while maintaining color detection capability.
Solution Approach 2:
The patent introduces computational processing as an intermediary between light capture and color image formation. Rather than using optical filters (Bayer array) to separate colors, the system uses software-based color assignment algorithms that process monochrome frames captured under periodic RGB illumination. This intermediary computational step achieves color detection without the light loss inherent in optical filtering.
3Illumination intensity
If external illuminators are used to improve low light imaging, then image brightness is improved, but optical efficiency is very low due to wastage of majority of light collected by camera lens in color image sensors
Solution Approach 1:
The patent replaces the mechanical/optical Bayer filter system with a computational color assignment system. By removing the filter array that causes light wastage, the system achieves much higher optical efficiency where nearly all light reaching the sensor is utilized. The periodic RGB illumination combined with monochrome sensor capture and software-based color reconstruction eliminates the fundamental inefficiency of optical color filtering.
4Adaptability or versatility
If Bayer filter array with more green filters is used, then color image detection is enabled, but each pixel detects only about 20% of neutrally colored light and color signal crosstalk occurs between neighboring pixels
Solution Approach 1:
The patent extracts and removes the Bayer filter array from the imaging system. By eliminating the color filter mosaic that causes both light loss and color crosstalk, the system achieves superior light detection accuracy. The full sensor array captures monochrome information without filtering, and color is subsequently assigned computationally, ensuring that each pixel receives maximum light while color accuracy is maintained through processing rather than optical filtering.
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 achieves significantly improved light detection efficiency and spatial resolution, reducing noise and motion blur while maintaining high frame rates, by effectively replacing Bayer filters with a multicolor illuminator and monochrome sensor, resulting in clearer and more accurate color images in low light conditions.
Implementation Method 1
a multicolor light illuminator that cycles through the three colors
Implementation Method 2
an image sensor that detects the light and outputs an image frame
Data Source
AI summary
A camera for enhanced color imaging in a low light environment including: one or more illuminators for illuminating a R, a G, and a B light at different time periods; an image sensor for capturing R G and B image frames; and a processor configured to generate an intermediate color frame from each of the R, G and B image frames; determine moving pixels in the each of the intermediate color frames; determine a true color for the moving pixels in each intermediate color frame; generate a true color frame for each intermediate color frame by substituting color of the moving pixels with respective true colors of the moving pixels, in intermediate color frame; calculate scene color metrics from the true color frame or intermediate color frame; and adaptively adjust illumination of one or more of the R, G, and B lights to enhance a next frame.