Airborne Image Sensor with Temporal Shifting and Multi-Spectral Filter
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Solution Overview
Problem
Current image sensors using Bayer or CFA filters for satellite imaging face limitations in handling multiple spectral bands, require demosaic processing that increases computational resources, and are prone to aliasing, especially in high-resolution applications, which complicates image fusion and resolution management.
Innovation Solution
An image sensor with a temporal delay integration matrix and a multi-spectral filter featuring multiple filtering elements arranged in lines and columns, allowing for simultaneous acquisition of multi-spectral and panchromatic images without on-board demosaic treatment, and enabling access to more than three spectral bands through a signal processing circuit that alternately acquires and processes images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If Bayer or CFA filters are used for color image acquisition, then color information can be obtained, but demosaicing processing is required which increases computational resources and processing complexity
Solution Approach 1:
The sensor divides the detection area into multiple spectral zones, with each zone dedicated to detecting a specific spectral band. This segmentation allows direct multi-spectral image acquisition without requiring demosaicing operations, as each pixel directly measures its assigned spectral band rather than requiring computational reconstruction of color information.
Solution Approach 2:
The sensor design integrates multiple spectral detection capabilities within a single detector matrix, enabling simultaneous acquisition of multiple spectral bands (including visible and SWIR ranges) without requiring separate sensors or post-processing fusion operations.
2Measurement precision
If high-resolution satellite images are acquired with multiple spectral bands, then image quality improves, but the volume of acquired images increases requiring compression and additional computing resources
Solution Approach 1:
The detector is divided into multiple independent spectral zones, each capturing a specific spectral band at full resolution. This allows the system to acquire high-resolution multi-spectral images directly without needing to store multiple color channels per pixel, reducing the overall data volume while maintaining measurement precision.
3Adaptability or versatility
If more than three spectral bands are required for space observation missions, then spectral coverage improves, but Bayer filter limitation to three colors becomes a constraint
Solution Approach 1:
The sensor divides the detection matrix into multiple spectral zones, with each zone configured for a specific spectral band. This segmentation approach allows the sensor to detect more than three spectral bands (including SWIR bands) by assigning dedicated detection regions to each band, overcoming the three-color limitation of traditional Bayer filters.
Solution Approach 2:
Different regions of the detector are assigned different spectral sensitivities based on local requirements. Each spectral zone is optimized for its specific band, allowing the overall sensor to provide versatile spectral coverage while maintaining simple filter configurations in each local region.
4Measurement precision
If linear detectors with TDI are used, then signal-to-noise ratio improves, but image geometry control becomes more difficult compared to matrix sensors
Solution Approach 1:
The invention merges the advantages of both linear TDI detectors and matrix sensors by implementing a matrix detector with time-shift and summation capability. Each column of pixels operates as a TDI unit, accumulating signals over time while maintaining the matrix structure's ability to capture complete image frames, thus achieving both high signal-to-noise ratio and precise geometric control.
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 solution reduces computational load, minimizes aliasing, and enhances image resolution by allowing simultaneous acquisition and processing of multiple spectral bands, facilitating efficient image fusion and improved spatial observation capabilities.
Implementation Method 1
linear detectors with time delay integration (TDI) are used to improve the signal-to-noise ratio
Implementation Method 2
image detection matrix comprises N > 1 rows and MC > 1 columns of photosensitive pixels
Implementation Method 3
a multispectral filter is placed in front of said or each detection matrix, said filter comprising several filtering elements arranged in rows and columns, and chosen from a plurality of types of filtering elements characterized by respective spectral transmission bands
Data Source
Figure 1~2
Figure 3
Figure 4a~4b
AI summary
Disclosed is an image sensor able to be embedded on board a carrier travelling above a scene to be observed, said sensor comprising at least one image detection matrix based on temporal shifting for summation comprising a plurality of photosensitive pixels aligned along the direction of travel of said carrier; and a circuit for processing the signals, having an input linked to a data output of said image detection matrix, said circuit being configured to provide at its output, for each instant of acquisition of said sensor, an image data matrix obtained by summation of image data generated by the rows of pixels; the sensor being characterized in that a multi-spectral filter is placed in front of said detection matrix, said filter comprising several filtering elements, arranged in rows and columns, characterized by respective spectral transmission bands, and each column of said detection matrix comprising at least one filtering element of each type of filtering element present on the whole of said filter.