Hyperspectral Image Data Processing for Real-Time Atmospheric Correction

Solution Overview

Problem

Hyperspectral imaging techniques face challenges in accurately discriminating objects due to atmospheric degradation and the need for extensive data and slow calculation of statistics, limiting their application in real-time and high-speed scenarios.

Innovation Solution

A data processing method that involves sequentially receiving and processing hyperspectral image data in portions, calculating and updating global and local statistical parameters, and applying correction factors to maintain accurate data correction and synchronization, facilitating efficient object detection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If atmospheric correction techniques are applied to improve object discrimination accuracy, then measurement precision is improved, but processing time increases and productivity decreases

Engineering Contradiction:

Improveobject discrimination accuracyVSAvoidprocessing speed

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent divides the hyperspectral image data into multiple data portions and processes them sequentially in a buffered manner. Statistical parameters are calculated incrementally as each data portion is received, rather than waiting for complete data acquisition. This segmentation allows the system to provide correction results in real-time while maintaining accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent calculates global statistical parameters and correction factors using an initial data set before processing individual data portions. This preliminary calculation of correction factors enables rapid correction of subsequent data portions without requiring repeated full-statistic calculations, significantly improving processing speed while maintaining correction accuracy.

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If large amounts of data are collected to calculate accurate statistics, then measurement precision is improved, but the time required for calculation increases

Engineering Contradiction:

Improvestatistical parameter accuracyVSAvoidcalculation time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent calculates global statistical parameters and correction factors using an initial data set before processing individual data portions. This preliminary calculation of correction factors enables rapid correction of subsequent data portions without requiring repeated full-statistic calculations, significantly improving processing speed while maintaining correction accuracy.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent implements a feedback mechanism where global statistical parameters are continuously updated using local statistical parameters calculated from received data portions. This running update allows the system to maintain accurate statistics over time without recalculating from scratch, reducing computation time while preserving accuracy.

Inventive Principle:

Principle #23Feedback

3Measurement precision

If block-oriented processing is used for atmospheric compensation, then correction accuracy is improved, but processing speed decreases

Engineering Contradiction:

Improvecorrection accuracyVSAvoidprocessing speed

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent divides the hyperspectral image data into multiple data portions and processes them sequentially in a buffered manner. Statistical parameters are calculated incrementally as each data portion is received, rather than waiting for complete data acquisition. This segmentation allows the system to provide correction results in real-time while maintaining accuracy.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentEP3080776B1Data processing method

Publication Date: 2019.01.09 BAE SYSTEMS PLC

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AI summary

A data processing method is disclosed for processing hyperspectral image data of a scene. The method comprises sequentially receiving portions of the data at a data buffer to form a data set comprising a predefined number of data portions and calculating a set of global statistical parameters and data correction factors using the data forming the data set. The method further comprises receiving a further data portion at the data buffer and simultaneously removing the earliest received data portion at the data buffer, from the data set, and subsequently calculating a set of local statistical parameters using the data of the further data portion. The method further comprises updating the set of global statistical parameters using the set of local statistical parameters and correcting the data of the data portion removed from the data set using the correction factors. The method further comprises outputting the corrected data portion and set of global statistical parameters calculated using the data set comprising the removed data portion, to a processor.