Image Sensor Pixel Array Segmentation for Frame Rate and Power
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Solution Overview
Problem
Current image sensors with multi-color filter arrays face challenges in improving frame rate and reducing analog power consumption while effectively converting light into perceivable image information, particularly in high-illuminance environments and in generating accurate color images.
Innovation Solution
The image sensor employs a pixel array with distinct pixel groups sharing floating diffusion regions, performing specific sum operations to generate raw images, and then extracts a white image and compensates for crosstalk to produce a Bayer image, optimizing the image processing workflow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a multi-color filter array is used in the image sensor, then color image capture capability is improved, but frame rate and analog power consumption are worsened
Solution Approach 1:
The pixel array is segmented into multiple pixel groups (first pixel groups and second pixel groups) with different color filter configurations. First pixel groups contain pixels with red, green, and blue color filters, while second pixel groups contain pixels with different color filter arrangements. This segmentation allows independent processing and readout of different color channels, enabling higher frame rates while maintaining color capture capability.
Solution Approach 2:
The image sensor employs periodic readout operations where first pixel data is read out in a first readout operation and second pixel data is read out in a second readout operation. This periodic action allows the sensor to cycle through different pixel groups systematically, improving frame rate by distributing the readout load across multiple operations rather than processing all pixels simultaneously.
2Measurement precision
If a multi-color filter array is used in the image sensor, then color image capture capability is improved, but analog power consumption is worsened
Solution Approach 1:
By segmenting the pixel array into distinct pixel groups with different color filter configurations, the analog processing can be performed in parallel on separate groups, reducing the total analog processing time and power consumption. Each pixel group can be processed independently, allowing for more efficient power management.
Solution Approach 2:
The periodic readout operations allow the analog processing circuitry to process different pixel groups at different times, reducing peak power consumption and allowing for more efficient power management. The analog-to-digital conversion and signal processing can be distributed across multiple periodic operations rather than requiring continuous high-power processing.
3Measurement precision
If white pixels are used to improve sensing sensitivity, then sensitivity is improved, but crosstalk between pixels is worsened
Solution Approach 1:
White pixels are confined to specific pixel groups (second pixel groups) rather than being distributed throughout the entire array. This segmentation allows white pixels to achieve high sensitivity in their designated regions while color pixels in first pixel groups maintain color accuracy. The separation reduces crosstalk by limiting the interaction between white pixels and color pixels to specific, controlled regions.
Solution Approach 2:
Different regions of the pixel array are assigned different functional qualities: first pixel groups are optimized for color capture with red, green, and blue filters, while second pixel groups are optimized for high sensitivity with white pixels. This local quality differentiation allows each region to perform its specialized function optimally while minimizing negative interactions between different pixel types.
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 frame rate and reduces analog power consumption while improving image quality by efficiently converting light into perceivable data and accurately generating color images.
Implementation Method 1
An image sensor included in a smartphone, a tablet personal computer (PC), or a digital camera obtains image information about an external object by converting a light reflected from the external object into an electrical signal
Data Source
AI summary
An image sensor includes a pixel array including a plurality of pixels; a row driver configured to control the plurality of pixels; and an analog-to-digital converter configured to digitize a result sensed by the pixel array to generate a first image, wherein the pixel array includes: first pixel groups, wherein each first pixel group of the first pixel groups includes first white pixels and first color pixels among the plurality of pixels; and second pixel groups, wherein each second pixel group of the second pixel groups includes second white pixels and second color pixels among the plurality of pixels, and wherein first pixel data of the first image are generated based on the first white pixels and the first color pixels, and second pixel data of the first image are generated based on the second color pixels.