Spatial Light Modulation for High-Resolution Depth Mapping
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Solution Overview
Problem
Current 3D scene acquisition techniques face challenges in spatial resolution, range accuracy, and cost-effectiveness, with camera-based methods suffering from poor range resolution and high noise sensitivity, while active range acquisition systems like LIDAR and TOF cameras have low spatial resolution due to limitations in 2D scanning and sensor array fabrication.
Innovation Solution
The use of spatial light modulation to modulate light pulses or reflected light before detection, combined with parametric signal deconvolution and convex optimization, allows for the generation of high-resolution depth maps using fewer sensors and simpler circuit elements, reducing power consumption and minimizing the impact of ambient light.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If LIDAR systems or TOF cameras are used for real-time range acquisition, then noise robustness and real-time operation are improved, but spatial resolution deteriorates due to limitations in scanning resolution and sensor array pixel count
Solution Approach 1:
The patent transforms the spatial resolution problem by moving from direct 2D sensor array mapping to a temporal dimension approach. Multiple 1D depth profiles are acquired over time with different spatial modulations and combined to reconstruct high-resolution 2D depth maps, effectively trading temporal processing for spatial resolution enhancement.
Solution Approach 2:
The patent segments the 2D spatial resolution requirement into multiple 1D depth profile measurements taken at different times with different spatial modulations. Each temporal measurement captures partial spatial information, and the segmentation is reversed through computational synthesis to achieve full 2D high-resolution depth maps.
2Measurement precision
If more pixels are used in TOF camera sensors to improve spatial resolution, then measurement precision is improved, but device complexity and manufacturing difficulty increase due to fabrication process limitations
Solution Approach 1:
The patent creates virtual copies of spatial information through temporal sampling and computational reconstruction. Instead of physically increasing the sensor array, the system captures multiple temporal copies of depth information with different spatial modulations and synthesizes them computationally to achieve equivalent or superior spatial resolution.
Solution Approach 2:
The patent changes the operational parameters of the TOF system by introducing temporal modulation patterns and spatial light modulation sequences. These parameter changes enable the extraction of high-resolution spatial information from temporal measurements, bypassing the physical pixel count limitation.
3Measurement precision
If computer vision techniques are used to acquire depth information, then spatial resolution can be improved, but computation intensity and sensitivity to scene texture increase
Solution Approach 1:
The patent replaces complex computational vision algorithms with a more efficient physics-based measurement approach. By using temporal TOF measurements with spatial modulations and applying straightforward signal processing (傅里叶变换 and optimization), the system achieves high spatial resolution without the heavy computational burden of traditional computer vision methods.
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
This approach achieves better spatial resolution in depth maps than conventional methods, consumes less power, and is suitable for applications with limited energy availability, such as handheld devices, while maintaining robustness against noise and ambient light.
Implementation Method 1
spatial light modulation is used to either modulate a series of light pulses transmitted toward the scene of interest or modulate the light reflected by the scene before it is incident on a time-resolved sensor
Implementation Method 2
Both LIDAR and TOF cameras operate by measuring the time elapsed between transmitting a pulse and sensing a reflection from the scene
Implementation Method 3
The reflected light from the scene, with time delay proportional to distance, is focused at a 2D array of TOF range sensing pixels
Data Source
AI summary
Depth information about a scene of interest is acquired by illuminating the scene, capturing reflected light energy from the scene with one or more photodetectors, and processing resulting signals, in at least one embodiment, a pseudo-randomly generated series of spatial light modulation patterns is used to modulate the light pulses either before or after reflection.