Spectral-Spatial-Temporal Image Detection Filtering
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Solution Overview
Problem
Existing optical sensor systems in military threat detection face challenges in accurately filtering out false detections while efficiently processing spectral, spatial, and temporal signature elements of launched ordnance, often requiring multiple filtering steps that tax processing resources or allow false positives.
Innovation Solution
A method involving spectral differencing, spatial filtering using a median filter, and temporal filtering with a predictive frame difference to generate a spectral-spatial-temporal filtered image, which is then thresholded for detection, optimizing the processing of optical sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple separate filtering steps are applied to spectral, spatial, and temporal data, then detection accuracy is improved, but processing resource consumption increases
Solution Approach 1:
The patent combines spectral, spatial, and temporal filtering operations into a single integrated filtering step. Instead of applying three separate filtering passes to the data, the system performs one simultaneous filter operation that processes all three signature elements together, thereby maintaining detection accuracy while reducing processing resource consumption.
Solution Approach 2:
The filtering operation is designed to perform multiple functions simultaneously: it filters spectral ratios, spatial characteristics, and temporal patterns in a single pass. This multi-functional approach eliminates the need for separate filtering steps for each signature element, optimizing processing efficiency while preserving comprehensive detection capability.
2Reliability
If multiple separate filtering steps are applied to spectral, spatial, and temporal data, then false detection filtering is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple filtering operations into a single unified filter that processes spectral, spatial, and temporal data simultaneously. This integration reduces the complexity of implementing and managing multiple separate filtering steps while maintaining the ability to effectively filter false detections across all three signature elements.
Solution Approach 2:
The system changes the parameter space by processing multiple signature elements (spectral, spatial, temporal) in a unified operation rather than sequentially. This parameter transformation approach simplifies the processing architecture while preserving the comprehensive false detection filtering capability.
3Measurement precision
If separate filtering is applied to each signature element, then spectral ratio filtering is improved, but processing time increases
Solution Approach 1:
The patent combines spectral filtering with spatial and temporal filtering into a single operation. By processing all three signature elements simultaneously rather than sequentially, the system maintains precise spectral ratio filtering while eliminating the time loss associated with multiple separate filtering passes.
Data Source
AI summary
A method of spectral-spatial-temporal image detection is disclosed. In one embodiment, a spectrally differenced image is obtained by computing a difference of at least two intensity values in at least two spectral bands of an image. Further, a spatially filtered spectral image is obtained by applying a spatial median filter to the obtained spectrally differenced image. Furthermore, a temporal image is obtained by determining a temporal pixel value difference using a computed predictive frame difference. In addition, a spectral-spatial-temporal filtered image for detection is obtained by using the obtained spatially filtered spectral image and the temporal image.