Spectral Imaging Filter and Tensor Restoration for Unified RGB Output
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Solution Overview
Problem
Conventional spectral imaging devices struggle to unify RGB images and spectral images in real-time, leading to inconsistencies in color representation.
Innovation Solution
A spectral imaging device that outputs at least two spectral images in parallel, utilizing a filter, image sensor, and data processing unit to achieve structural unification, with the aid of a standard spectrum and restoring tensor for high-speed, accurate spectral restoration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate RGB imaging module is used, then RGB imaging capability is achieved, but temporal and spatial unification with spectral imaging is lost
Solution Approach 1:
The patent merges the spectral imaging function and RGB imaging function into a single integrated imaging device. The filter module and image sensor work together to simultaneously capture spectral data and generate RGB images from the same incident light, ensuring temporal and spatial unification between spectral and RGB imaging results.
2Loss of information
If multi-spectral image computation method is used, then spectral information is obtained, but color realism of RGB image is insufficient
Solution Approach 1:
The patent segments the imaging process into distinct functional modules: a filter module that separates incident light into spectral bands, and an image sensor that captures the modulated light. This segmentation allows direct optical generation of RGB images from spectral components, preserving color realism while obtaining spectral information.
Solution Approach 2:
The filter acts as an intermediary that modulates incident light before it reaches the image sensor. By using optical filters with specific transmission characteristics, the system directly generates RGB images with accurate color representation from the spectral decomposition of light, rather than computing RGB from multi-spectral data.
3Adaptability or versatility
If parallel spectral image output is implemented, then structural unification is achieved, but device complexity increases
Solution Approach 1:
The imaging device is designed with multi-functionality, where a single filter module and image sensor combination can simultaneously perform spectral imaging and RGB imaging. The filter's transmission characteristics enable it to serve multiple purposes: spectral decomposition for spectral imaging and color filtering for RGB image generation, reducing overall device complexity.
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
Enables simultaneous output of high-quality spectral and RGB images, ensuring consistent color representation without deviation, and allows for adjustable spatial, temporal, and spectral resolutions.
Implementation Method 1
a filter for modulating incident light
Implementation Method 2
an image sensor for receiving the modulated incident light to obtain an output signal
Data Source
AI summary
The present application relates to a spectral restoring method including: receiving and modulating incident light by a filter included in a spectral imaging device; acquiring a light energy response signal matrix output by an image sensor of the spectral imaging device and a standard spectrum; determining a primitive restoring function and a response signal vector of the primitive restoring function based on the light energy response signal matrix, the primitive restoring function restoring a spectral image value of a predetermined channel corresponding thereto using a predetermined pixel value of the photosensitive chip and pixel values in the vicinity thereof; acquiring a restoring tensor, the product of the restoring tensor and the response signal vector being equal to an output of the primitive restoring function based on the response signal vector; and obtaining a restored spectral image based on the product of the restoring tensor and the response signal vector.