Time-of-flight Imaging of Occluded Layers via Kurtosis Filtering
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Solution Overview
Problem
Conventional imaging techniques face challenges in capturing clear images of occluded layers in multi-layered objects due to decreasing signal-to-noise ratio with increasing depth, low contrast, and occlusion by front layers, especially in THz-TDS imaging.
Innovation Solution
A time-of-flight imaging system that uses kurtosis filtering in the frequency domain and time-windowing to enhance contrast and mitigate occlusion, allowing the system to capture images of occluded layers by analyzing each layer separately and averaging high-kurtosis frequency frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional imaging techniques are used to capture images of occluded layers, then the imaging system can operate with simple hardware, but the signal-to-noise ratio decreases with increasing depth and image contrast is low
Solution Approach 1:
The patent applies preliminary action by performing kurtosis filtering on the time-domain signal before image reconstruction. The system pre-processes the raw ToF data by calculating kurtosis values for different time windows, identifying regions with high kurtosis that correspond to occluded layers, and selectively enhancing these regions before final image formation. This preliminary enhancement of relevant signals improves the signal-to-noise ratio for deep occluded layers without requiring complex hardware modifications.
2Measurement precision
If conventional imaging techniques are used, then the system structure remains simple, but the contrast of occluded layer images is low and occlusion by front layers persists
Solution Approach 1:
The patent implements local quality by applying kurtosis-based enhancement selectively to specific time windows corresponding to occluded layers, rather than uniformly processing the entire signal. The system calculates kurtosis values for different time segments, identifies regions with high kurtosis (indicating occluded layer reflections), and applies enhancement only to these localized regions. This targeted approach improves image contrast for occluded layers while maintaining simplicity in non-occluded regions.
3Measurement precision
If the imaging system captures all layers simultaneously, then the capture process is efficient, but occluded layers cannot be distinguished from front layers
Solution Approach 1:
The patent applies segmentation by dividing the time-domain signal into multiple time windows, each corresponding to a specific layer depth. The system segments the reflected light signal based on time-of-flight information, assigning different time intervals to different layers. By calculating kurtosis values for each segmented time window and selectively enhancing high-kurtosis segments, the system achieves clear differentiation of occluded layers from front layers while maintaining efficient simultaneous capture of all layers.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution effectively enhances contrast and reduces occlusion, enabling clear image capture of occluded layers even when they are partially transmissive and reflective, overcoming the limitations of conventional imaging techniques.
Implementation Method 1
each layer of the multi-layered object partially reflects and partially transmits light at the frequency emitted by the ToF sensor
Implementation Method 2
each layer of the multi-layered object partially reflects and partially transmits light at the frequency emitted by the ToF sensor
Implementation Method 3
A time-of-flight imaging system that uses kurtosis filtering in the frequency domain and time-windowing to enhance contrast and mitigate occlusion
Data Source
AI summary
A sensor may measure light reflecting from a multi-layered object at different times. A digital time-domain signal may encode the measurements. Peaks in the signal may be identified. Each identified peak may correspond to a layer in the object. For each identified peak, a short time window may be selected, such that the time window includes a time at which the identified peak occurs. A discrete Fourier transform of that window of the signal may be computed. A frequency frame may be computed for each frequency in a set of frequencies in the transform. Kurtosis for each frequency frame may be computed. A set of high kurtosis frequency frames may be averaged, on a pixel-by-pixel basis, to produce a frequency image. Text characters that are printed on a layer of the object may be recognized in the frequency image, even though the layer is occluded.