CMYW Image Sensor Layout for RGB and Near-IR Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current image sensing devices face challenges in achieving improved performance and efficiency in processing image signals, particularly in extracting red, green, blue, and near-infrared data components from light signals.
Innovation Solution
The proposed image sensing device incorporates a lens module, microlenses, and an image sensor with cyan, magenta, yellow, and white pixels, along with an image signal processor that uses color filters to generate and extract these data components from light signals, enabling enhanced signal processing and noise reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image sensors with standard color filters (RGB) are used, then the device structure is simple, but the ability to extract near-infrared data components and improve signal-to-noise ratio is limited
Solution Approach 1:
The sensor divides the pixel array into multiple regions, each equipped with different color filters (cyan, magenta, yellow, and white/black). This segmentation allows each pixel type to capture specific wavelength ranges, enabling simultaneous extraction of color and near-infrared data components through specialized filtering rather than requiring complex post-processing of generic RGB data
Solution Approach 2:
Different regions of the sensor are assigned different color filter characteristics tailored to their specific measurement functions. Cyan, magenta, and yellow filters are optimized for capturing specific color components, while white filters capture broader spectrum including near-infrared. This local optimization of filter properties enhances the precision of extracting specific data components without requiring the entire sensor to be complex
2Reliability
If multiple color filters are used to extract multiple data components, then the signal-to-noise ratio improves, but the device complexity increases
Solution Approach 1:
The sensor merges multiple color filter types (cyan, magenta, yellow, white) within a single sensor array, allowing simultaneous capture of multiple wavelength components. This combining approach enables robust signal extraction for both color and near-infrared data in one integrated device, improving reliability without requiring separate sensors for each function
Solution Approach 2:
The sensor achieves multi-functionality by incorporating diverse color filters that can simultaneously perform color imaging and near-infrared detection. The same sensor array processes multiple data components (color and near-infrared) through its multi-filter architecture, eliminating the need for separate specialized sensors and improving signal-to-noise ratio across multiple measurement domains
3Measurement precision
If a white pixel without color filter is used to capture near-infrared light, then the near-infrared data extraction is improved, but the color accuracy for that pixel is reduced
Solution Approach 1:
The sensor segments the pixel array so that only specific white pixels (without color filters) are dedicated to near-infrared capture, while other pixels with cyan, magenta, and yellow filters handle color imaging. This segmentation ensures that color information is preserved in the filtered pixels while near-infrared precision is optimized in the white pixels
Solution Approach 2:
The sensor uses the white pixels as intermediary elements specifically for near-infrared detection, while relying on the colored pixels for color information. The image processing unit acts as a mediator, combining data from both white and colored pixels to reconstruct complete color and near-infrared information, thus compensating for the color information loss in white 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 improves the signal-to-noise ratio and allows for effective extraction of color and near-infrared data components, enhancing the overall performance of the image sensing device in various lighting conditions.
Implementation Method 1
filtering a first light through a lens module to obtain a second light
Implementation Method 2
generating, by an image sensor, a first image signal using a first portion of the second light received through a cyan color filter
Implementation Method 3
An image sensing device may be manufactured using a semiconductor element that converts optical information into an electric signal
Data Source
AI summary
An image sensing device and a method of image signal processing are provided. The image sensing device includes a lens module, a microlens below the lens module, an image sensor below the microlens and which includes a first pixel having a cyan color filter, and which outputs a first image signal, a second pixel having a magenta color filter, and which outputs a second image signal, a third pixel having a yellow color filter, and which outputs a third image signal, and a fourth pixel which outputs a fourth image signal, and an image signal processor which receives image signals of the image sensor, and extracts a red (R) data component, green (G) data component, blue (B) data component, and near-infrared (IR) data component of the light from the image signals.