Hyperspectral Imaging Software Configuration Modularization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for creating data processing and visualization flows for hyperspectral imaging devices are cumbersome and require case-by-case programming, limiting their application to single hardware platforms and making it difficult to adapt for different environments.
Innovation Solution
A computer-implemented method and system for defining a software configuration that separates hyperspectral image processing functionalities from hardware-specific functions, allowing for modular creation and reuse of applications across different hardware implementations, enabling easier adaptation and collaboration between specialists.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If case-by-case programming is used to create data processing flows, then the application can be customized for specific hardware, but the development time and complexity increase significantly
Solution Approach 1:
The patent segments the data processing flow into modular functional blocks that can be independently configured and reused. Each processing step (acquisition, preprocessing, processing, visualization) is separated into discrete, configurable modules that can be assembled through software configuration rather than programming, enabling rapid adaptation to different hardware platforms.
Solution Approach 2:
The patent creates a universal configuration framework that can be applied across multiple hardware platforms. The same data processing flow configuration can be transferred between different hyperspectral imaging devices through the standardized configuration file format, eliminating the need for case-by-case programming and significantly reducing development time.
2Reliability
If detailed programming is performed for each hardware platform, then hardware-specific optimization is achieved, but the system complexity and difficulty of collaboration increase
Solution Approach 1:
The patent introduces a configuration file as an intermediary layer between the hardware platform and the data processing logic. This configuration file contains platform-specific parameters and settings that allow the same processing flow to be adapted to different hardware without modifying the underlying code, thus maintaining hardware-specific optimization while reducing software complexity.
Solution Approach 2:
The patent separates hardware-specific configuration parameters from the universal data processing logic. By segmenting the system into platform-independent processing modules and platform-specific configuration files, the software complexity is reduced while maintaining the ability to optimize for specific hardware platforms.
3Measurement precision
If custom programming is done for each application, then specific processing requirements are met, but the ease of operation and reusability decrease
Solution Approach 1:
The patent implements pre-configured functional blocks and templates for common data processing tasks. These pre-built modules contain standardized processing algorithms and parameters that can be directly applied to meet specific processing requirements without requiring custom programming, thus improving ease of operation while maintaining processing accuracy through proven algorithms.
Solution Approach 2:
The patent creates universally applicable processing modules that can handle multiple processing requirements through configuration rather than custom code. The same functional blocks can be reused across different applications and hardware platforms, reducing the need for custom programming while maintaining the ability to meet specific processing requirements through parameter adjustment.
Data Source
AI summary
A method of defining a software configuration for a hyperspectral imaging apparatus includes: creating a plurality of different functionalities, each based on at least one wavelength range; storing one or more of the created functionalities into a hyperspectral image processing model; generating a hyperspectral application for a specific hardware implementation of the hyperspectral imaging apparatus by configuring the hyperspectral application to utilize one or more of the created functionalities of the hyperspectral image processing model; and setting a selection of wavelengths as a control parameter in the hyperspectral application for controlling the specific hardware implementation of the hyperspectral imaging apparatus during an image capture. The selection of wavelengths is based on the wavelength ranges of the utilized one or more created functionalities.