Single-Photon Depth Imaging With Compressive Histograms
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Solution Overview
Problem
Existing single-photon depth imaging systems generate large amounts of data, leading to impractical data rates that exceed the bandwidth of current data-transfer standards, particularly in applications requiring high depth resolution and frame rates.
Innovation Solution
Implementing compressive histograms using a coding matrix to encode photon arrivals, allowing for efficient generation and reduction of data rates without sacrificing depth resolution, by mapping time bins of the full histogram onto multiple 'compressive bins' through an encoding process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full histogram capture is used to maintain high depth resolution, then measurement precision is improved, but productivity deteriorates due to excessively high data rates
Solution Approach 1:
The patent extracts only the essential information needed for depth resolution from the full histogram. By using compressive histogramming with carefully designed coding matrices, the system extracts depth information while discarding redundant temporal details, achieving a balance between measurement precision and data rate reduction.
Solution Approach 2:
Instead of reducing histogram resolution and then trying to recover depth information, the patent inverts the approach by using wide pulses and compressive sensing to directly achieve high depth resolution from compressed histograms. This inversion allows maintaining measurement precision while inherently reducing data rates.
2Productivity
If high frame rates are used to capture fast-moving objects, then productivity is improved, but loss of information worsens due to reduced time per frame
Solution Approach 1:
The patent performs preliminary encoding of temporal information into compressive histograms during photon accumulation. By pre-processing the temporal data through coding matrices before readout, the system preserves essential temporal information even at high frame rates where individual frame integration time is reduced.
Solution Approach 2:
The patent changes the parameter representation from full temporal histograms to compressive histogram bins. This parameter transformation allows the system to capture fast-moving objects at high frame rates while preserving sufficient temporal information for depth resolution through the mathematical properties of compressive sensing.
3Productivity
If coarse histogramming is used to reduce data rates, then productivity is improved, but measurement precision deteriorates due to low time resolution
Solution Approach 1:
The patent fundamentally changes the parameter representation by using compressive histogramming with coding matrices instead of simple coarse binning. This parameter transformation allows the system to achieve both data rate reduction and high depth resolution simultaneously, overcoming the limitation of traditional coarse histogramming.
Solution Approach 2:
The patent combines multiple techniques into a composite approach: wide laser pulses, compressive histogramming with optimized coding matrices, and sub-bin processing. This composite methodology achieves data rate reduction while maintaining measurement precision, neither of which can be achieved by coarse histogramming alone.
4Measurement precision
If wide pulses are used to improve depth resolution with compressive histograms, then measurement precision is improved, but loss of energy worsens due to reduced peak intensity
Solution Approach 1:
The patent changes the pulse parameter from narrow high-intensity to wide lower-intensity pulses, but compensates through compressive histogramming and signal processing. This parameter transformation allows maintaining measurement precision while reducing peak energy requirements, addressing the energy loss concern.
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
Reduces data rates by 1-2 orders of magnitude compared to full histogram capture, while maintaining high depth resolution and visual quality, making it feasible with existing data transfer standards like USB and PCIe.
Implementation Method 1
a light source configured to send out light pulses periodically
Implementation Method 2
the first detected photon is not necessarily the first photon that is incident on the SPAD, as some photons that are incident will not be detected (the proportion of incident photons detected is sometimes referred to as the quantum efficiency of the detector), and some detections result from noise rather than an incident photon
Implementation Method 3
Detectors that are capable of detecting the arrival time of an individual photon, such as single-photon avalanche diodes (SPADs)
Data Source
AI summary
In accordance with some embodiments, systems, methods, and media for single photon depth imaging with improved efficiency using compressive histograms are provided. In some embodiments, the system comprises: a light source; a detector configured to detect arrival of individual photons; a processor programmed to: detect a photon arrival; determine a time bin i of the photon arrival in a range from 1 to N a total number of time bins; update a compressed histogram comprising K stored values representing bins of the compressed histogram based on K values in a code word represented by an ith column of a coding matrix C having dimension K×N, with each column different than each other column, and each column corresponds to a single time bin i; and estimate a depth value based on the K values.