Color Image Reconstruction via Spectral Conversion Matrix
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Solution Overview
Problem
The existing methods for medical diagnosis using light sources with different spectra are impractical due to the need for multiple expensive hardware setups, maintenance, and complex operation, making it difficult to effectively detect pathological changes such as those caused by enterovirus in children.
Innovation Solution
A method that uses a spectrum-acquiring device to calculate a conversion matrix for digital images, allowing the simulation of different light sources to enhance chromatic differences and facilitate diagnostic judgment, reducing the need for multiple light sources and improving detection capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple light sources with different spectra are provided to generate different biological images, then diagnostic capability is improved, but hardware cost, maintenance complexity, and operational difficulty increase significantly
Solution Approach 1:
The patent uses a spectrum-acquiring device to capture the spectral characteristics of different light sources, then stores these spectra as digital data. Instead of physically replacing light sources, the system copies their spectral properties into a database and uses computational methods to simulate their effects on digital images, thereby achieving the diagnostic benefits of multiple light sources without the associated hardware complexity
Solution Approach 2:
The patent replaces the mechanical/physical system of multiple actual light sources with a computational system. By acquiring spectral data and using matrix operations to transform digital images according to different light source spectra, the system substitutes physical light source replacement with digital signal processing, eliminating the need for multiple physical devices while maintaining diagnostic capability
2Adaptability or versatility
If various lighting equipment are provided to serve as light sources with different spectra, then different biological images can be obtained, but accommodation space and operational expertise requirements increase
Solution Approach 1:
The patent creates a universal system where a single digital camera and spectrum-acquiring device can perform the function of multiple specialized light sources. By building a database of different light source spectra and using computational transformation, one piece of equipment gains the versatility of multiple devices, allowing operators to access various spectral conditions through software selection rather than physical device changes
Solution Approach 2:
The patent introduces a computational intermediary layer between the single light source and the digital camera. The spectrum database and conversion matrix act as mediators that translate the captured image data into what would have been captured under different light sources, thereby providing spectral variety without requiring operators to handle multiple physical lighting equipment
3Measurement precision
If multiple light sources are used to enhance chromatic difference for pathological detection, then detection accuracy is improved, but overall system cost increases
Solution Approach 1:
The patent replaces expensive, durable physical light sources with inexpensive digital spectral data stored in a database. Instead of investing in multiple costly light source devices, the system uses cheap digital representations of light spectra that can be freely accessed and transformed computationally, significantly reducing the quantity of capital required while maintaining detection accuracy
Data Source
AI summary
A method for reconstructing color images has steps of using a spectrum-acquiring device to acquire spectral data of a plurality of sample color blocks and calculating coefficients of a basis matrix of the sample color blocks; obtaining digital counts of the plurality of sample color blocks with a digital camera; obtaining a conversion matrix in accordance with the coefficients of the basis matrix and the digital counts; acquiring digital counts of an original image with the digital camera, and generating a reconstructed image in accordance with the digital counts of the original image and the conversion matrix; and varying the conversion matrix in accordance with a new light source, and computing to generate a reconstructed image corresponding to the new light source in accordance with the digital counts of the original image and the varied conversion matrix.