Spectral Geographic Information System Data Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The large amount of data generated by hyperspectral imaging technology makes analysis and display difficult and processor-intensive, necessitating a method to convert this data into a compact and efficient file structure for easier analysis and presentation.
Innovation Solution
A system that translates large hyperspectral image data into a compact Spectral Geographic Information System (SGIS) database structure, comprising a shape file portion, a hyperspectral global data portion, and a hyperspectral segment data portion, allowing for efficient analysis and display of target locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hyperspectral imaging technology is used to capture detailed spectral data, then measurement precision and information content are improved, but data volume and processing complexity increase significantly
Solution Approach 1:
The patent divides the hyperspectral image data into multiple segments or bands, processing and analyzing them separately. This segmentation allows the system to handle the large data volume in manageable portions while preserving the high spectral resolution information needed for precise material identification and target detection.
Solution Approach 2:
The patent extracts and isolates specific spectral features and signatures from the complete hyperspectral data cube. By extracting only the relevant spectral information needed for target detection and classification, the system reduces processing complexity and data volume while maintaining measurement precision for identifying materials such as camouflage, vegetation, and man-made objects.
2Loss of information
If hyperspectral image data is stored in detailed format, then information completeness is improved, but ease of operation and analysis speed deteriorate
Solution Approach 1:
The patent performs preliminary processing of hyperspectral data during the acquisition and storage phases, including spectral calibration, noise reduction, and organization into standardized data structures. This preliminary action prepares the data for rapid analysis later without losing spectral information, enabling faster target detection and classification when the data is queried.
Solution Approach 2:
The patent introduces intermediate data structures and processing layers that bridge the detailed spectral data and the analysis algorithms. These intermediaries organize spectral signatures, create lookup tables, and pre-compute spectral features, making the complete spectral information more accessible and easier to operate with during target detection and classification tasks.
3Measurement precision
If complete hyperspectral data is processed for target detection, then detection accuracy is improved, but productivity and processing time decrease
Solution Approach 1:
The patent applies partial processing by focusing computational resources on detecting and analyzing only those spectral regions and features that are most relevant to target detection. Rather than processing the entire hyperspectral data cube with equal intensity, the system identifies and concentrates analysis on areas containing potential targets, maintaining detection accuracy while improving processing speed and productivity.
Data Source
AI summary
A system for the conversion, analysis and display of geographic imaging data is provided which allows for the efficient location of various targets based on user selectable search criteria. The system provides a means to convert large image database information to a more compact and efficient structure employing the use of a shape library and an associated shape index.