Endoscope Green Light Sensor Pixel Density for Power Reduction
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Solution Overview
Problem
Endoscopes face challenges in capturing high-resolution medical images while minimizing power consumption and heat generation, particularly due to the high pixel count of red and blue image sensors, which leads to increased noise and power usage.
Innovation Solution
The endoscope employs a camera head with a high-resolution green light sensor and lower-resolution red and blue light sensors, with the latter utilizing a binning function to reduce pixel output, and a control unit that switches between normal and binning modes based on temperature and movement to optimize power usage and image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution image sensors are used for R, G, and B channels, then image resolution is improved, but power consumption and heat generation increase
Solution Approach 1:
The patent applies local quality by assigning different pixel densities to different color channels based on their specific requirements. The G channel uses high-resolution sensors (first number of pixels) to capture fine details, while the R and B channels use lower-resolution sensors (second number of pixels smaller than the first). This localized optimization ensures that high resolution is provided only where needed (green channel for detail verification) while reducing overall power consumption and heat generation from fewer total pixels being processed.
2Area of stationary object
If the image pickup element for R has the same light-receiving face size as G and B sensors, then sensor area is optimized, but pixel size becomes smaller and sensitivity decreases
Solution Approach 1:
The patent implements local quality by making the R and B sensors smaller in pixel count than the G sensor, which allows the R and B sensors to have larger individual pixel sizes despite the same overall light-receiving face area. This localized differentiation ensures that pixels in the R and B channels are sufficiently large to maintain sensitivity and signal-to-noise ratio, while the G channel maintains high resolution through its larger number of pixels.
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 configuration allows for the acquisition of high-resolution medical images with reduced power consumption and heat generation, while maintaining acceptable signal-to-noise ratios and image quality.
Implementation Method 1
a first sensor having pixels of a first number of pixels, the first sensor being configured to receive green (G) light that is light with a G wavelength band
Implementation Method 2
a second sensor having pixels of a second number of pixels smaller than the first number of pixels, the second sensor being configured to receive light different from the G light
Data Source
AI summary
An endoscope includes a camera head including a first sensor having a first number of pixels, the first sensor being configured to receive green (G) light that is light with a G wavelength band, a second sensor having a second number of pixels smaller than the first number of pixels, the second sensor being configured to receive red (R) light that is light with a R wavelength band, and a third sensor having a third number of pixels smaller than the first number of pixels, the third sensor being configured to receive blue (B) light that is light with a B wavelength band.