Image Sensor with Nested Color, Absorption and Polarization Filters
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Solution Overview
Problem
Current RGB image sensors struggle to reliably detect hazards like puddles, water, and ice on road surfaces due to limitations in distinguishing between absorption and polarization effects, leading to unreliable localization and classification results.
Innovation Solution
An image sensor with a grid pattern of pixels, incorporating multiple filter elements including color filters, absorption filters with different optical bandwidths, and polarization filters with distinct characteristics, which provide additional information beyond traditional color data to enhance detection capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If RGB image sensors are used for road condition detection, then the device remains compact and simple, but the ability to distinguish between water, snow, and ice is poor
Solution Approach 1:
The patent divides each image element into multiple sub-elements, with each sub-element containing different filter combinations (RGB filters, absorption filters, polarization filters). This segmentation allows the sensor to capture multiple types of optical information simultaneously without requiring separate sensor arrays, thereby improving detection reliability while maintaining reasonable device complexity.
Solution Approach 2:
Each image element is designed to perform multiple functions by incorporating different filter types (color filters for RGB information, absorption filters for material identification, polarization filters for surface property detection). This multi-functionality allows a single sensor array to provide comprehensive road condition analysis, resolving the contradiction between detection capability and device complexity.
2Loss of information
If multiple filter elements are added to each image element, then absorption and polarization information is obtained, but the surface area and resolution are affected
Solution Approach 1:
The patent nests multiple filter elements within each image element, creating a hierarchical structure where absorption filters, polarization filters, and color filters are arranged in nested patterns. This nesting allows multiple filter types to occupy the same spatial footprint, capturing comprehensive optical information without proportionally increasing the overall sensor surface area.
Solution Approach 2:
The patent transitions from traditional 2D filter arrangements to a multi-dimensional filter configuration where filters are arranged in multiple rows and columns within each image element. This dimensional expansion allows more filter elements to be packed into the same area, maintaining resolution while increasing information completeness.
3Loss of information
If multiple filter elements are added to each image element, then absorption and polarization information is obtained, but the manufacturing complexity increases
Solution Approach 1:
The patent applies different filter combinations to different regions of the sensor array, with each image element containing locally optimized filters based on the specific detection requirements. This local quality approach allows standardized manufacturing processes to be used while achieving customized detection capabilities, thereby reducing overall manufacturing complexity.
Solution Approach 2:
The patent uses parameter changes in filter arrangement and configuration to optimize performance. By varying the orientation, density, and type of filters in different image elements, the system achieves comprehensive information capture while maintaining compatibility with existing manufacturing processes, thus balancing information completeness with manufacturing simplicity.
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
The enhanced image sensor enables improved detection of road hazards by differentiating between water, snow, and black ice, and identifying organic materials, offering a compact and efficient solution for improved road condition recognition.
Implementation Method 1
The color filter is designed to filter light according to color, thus enabling the image sensor to detect color information
Implementation Method 2
Absorption information makes it easier to find specific materials with certain absorption properties in a sensor image
Implementation Method 3
sensor images with polarization filters make it possible to analyze the light rays reflected from a surface
Data Source
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AI summary
Exemplary embodiments of the invention provide an image sensor (100, 410, 650, 720) with an image element structure (100). The image element structure (100) comprises a plurality of image elements (120) arranged in a grid pattern in a first direction (113, 213) and in a second direction 116, which is orthogonal to the first direction (113, 213). Each image element (120) of the plurality of image elements (120) comprises a plurality of spatially adjacent filter elements (130, 133, 136, 242, 244, 246, 253, 256, 263, 266). The majority of filter elements (130, 133, 136, 242, 244, 246, 253, 256, 263, 266) have at least one color filter (133, 242, 244, 246) and at least one additional filter (136, 253, 256, 263, 266) from a filter group.The filter group comprises a first absorption filter (136, 253, 256) with a first optical bandwidth, a second absorption filter (136, 253, 256) with a second optical bandwidth that differs from the first optical bandwidth, a first polarization filter (136, 263, 266) with a first polarization characteristic, a second polarization filter (136, 263, 266) with a second polarization characteristic that differs from the first polarization characteristic, and a filter element (136) without absorption or polarization effect.