2D Imaging With PSF Deconvolution for Lightweight Range Measurement
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Solution Overview
Problem
Existing distance measurement systems are costly, complex, and bulky, making them unsuitable for many applications, and often suffer from ineffective processing times.
Innovation Solution
Utilizing standard commercial off-the-shelf imaging systems, time-varying laser illumination, and simple sensors like gyroscopes and accelerometers to determine distances based on point-spread-functions (PSFs) and deconvolve images to calculate distances, employing angular movement and jitter induction to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional distance measurement systems are used, then distance measurement capability is achieved, but device complexity and cost increase
Solution Approach 1:
The patent uses a standard 2D image capture system (copying existing technology) to obtain images, then applies computational methods to extract depth information. Instead of using complex 3D sensors, the system captures 2D images and processes them through point-spread-function analysis and deconvolution to generate depth maps, effectively copying depth measurement capability from complex hardware to software processing.
Solution Approach 2:
The patent replaces complex mechanical/optical 3D sensing systems with a combination of standard 2D imaging and computational algorithms. The system substitutes physical depth-sensing mechanisms with image processing techniques including PSF modeling, deconvolution, and artifact power analysis, thereby reducing device complexity while maintaining measurement capability.
2Measurement precision
If conventional distance measurement systems are used, then distance measurement capability is achieved, but system size and weight increase
Solution Approach 1:
The patent copies depth measurement functionality from heavy dedicated 3D sensors into lightweight 2D image capture systems combined with computational processing. By using standard camera hardware and algorithmic analysis instead of specialized depth-sensing components, the system achieves comparable functionality with significantly reduced weight.
3Measurement precision
If conventional distance measurement systems are used, then distance measurement capability is achieved, but processing time increases
Solution Approach 1:
The patent performs preliminary actions by capturing multiple images at different焦 planes (focus settings) before the final depth calculation. The system pre-processes images to identify in-focus regions and uses these preliminary results to guide subsequent depth map generation, reducing the computational burden and processing time for the final depth measurement.
Solution Approach 2:
The patent applies partial action by focusing computational resources only on regions of interest within the image. Instead of processing entire images at full resolution, the system identifies key features and processes only relevant areas, reducing overall processing time while maintaining measurement precision for critical depth information.
4Device complexity
If simple sensors are used, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent changes parameters by capturing images at multiple焦 planes (different focus distances) rather than using a single complex sensor. The system varies the optical parameters of the simple 2D camera to gather multiple measurements, then combines these through computational analysis to achieve precision comparable to complex dedicated sensors.
Solution Approach 2:
The patent implements feedback through an iterative process where the system analyzes image artifacts, adjusts its understanding of scene depth, and refines the depth map generation. The artifact power analysis provides feedback about the quality of deconvolution results, allowing the system to iteratively improve measurement precision using simple sensors.
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
Enables accurate distance measurement with simpler electronics, capable of producing 3D representations from 2D images, overcoming the limitations of conventional 3D LIDAR systems by using quasi-continuous wave illumination and known pixel technology.
Implementation Method 1
time-varying laser illumination
Implementation Method 2
determine distances based on point-spread-functions (PSFs) and deconvolve images
Implementation Method 3
determine distances based on point-spread-functions (PSFs)
Data Source
AI summary
In some embodiments, systems are provided to determine distances to one or more objects, and comprise an image capture system; an angular movement system; an illumination source providing illumination having a time varying amplitude; and a range measurement circuit configured to: obtain, based on at least one of measured and induced LOS angular displacement changes relative to the image capture system, a set of candidate point-spread-functions (PSFs) corresponding to different possible ranges; deconvolve, using the candidate PSFs, at least a region of interest (ROI) in an evaluation image to obtain at least a set of deconvolved ROIs of the evaluation image, each corresponding to one of the candidate PSFs; identify a first candidate PSF that produces a deconvolved ROI resulting in a determined artifact power that is lower than a corresponding artifact power determined from the other candidate PSFs; and determine a distance corresponding to the first candidate PSF.