Reflectance Distribution Mapping for LIDAR Accuracy
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Solution Overview
Problem
Conventional spectrometers are inadequate for determining the spectral reflectivity of real-world objects, especially non-flat objects with curvature, as they typically measure reflectance at a single angle and point, failing to capture the object's reflectance distribution effectively.
Innovation Solution
A reflectance measurement system that uses a combination of an emitting device, cameras, and optical elements to capture reflectance distribution mapping of entire objects in a single image, accounting for various angles and light properties such as wavelength and polarization, allowing for accurate reflectance data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a conventional spectrometer is used to measure reflectance, then the measurement is simple and quick, but it only captures reflectance at a single angle and point, failing to capture the reflectance distribution of non-flat objects
Solution Approach 1:
The patent divides the measurement task into multiple spectral images captured at different angles. Instead of using a single complex spectrometer setup, the system segments the measurement into multiple simpler captures, each contributing to the overall reflectance distribution map. This allows comprehensive angular coverage while maintaining system simplicity.
Solution Approach 2:
The patent transitions from single-point measurement to multi-point spatial mapping by capturing spectral images across the object surface. This adds spatial dimensionality to the measurement, creating a reflectance distribution map that covers the entire object rather than just a single point, thereby resolving the limitation of conventional spectrometers.
2Adaptability or versatility
If a spectrometer measures reflectance at a single point, then the measurement is straightforward, but it cannot capture the angle-dependent reflectivity (BRDF) of real-world objects
Solution Approach 1:
The patent performs preliminary capture of multiple spectral images at different angles before processing. By capturing all necessary angular data in advance through a series of rapid captures, the system prepares complete reflectance distribution information that can be processed efficiently, reducing overall measurement time while achieving comprehensive angular coverage.
Solution Approach 2:
The system creates multiple spectral copies of the object at different angles rather than sequentially measuring each angle with a single sensor position. This copying approach allows parallel data collection across multiple angles, significantly reducing measurement time while maintaining comprehensive angular coverage for BRDF characterization.
3Loss of information
If multiple spectral images are captured at different angles, then comprehensive reflectance distribution data is obtained, but the data processing and mapping complexity increases
Solution Approach 1:
The patent replaces complex mechanical multi-angle measurement systems with a computational approach. Instead of physically repositioning sensors or using complex optical mechanisms to capture angular variations, the system uses multiple fixed-angle spectral images and processes them computationally to generate the reflectance distribution map, thereby reducing mechanical complexity while maintaining information completeness.
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 the generation of comprehensive reflectance distribution maps for objects, improving the accuracy of LIDAR systems and other applications by providing detailed reflectance information at multiple angles and light conditions, enhancing the reliability of range determinations and object classification.
Implementation Method 1
an emitting device to illuminate the object at a particular wavelength
Implementation Method 2
a camera to capture an image of the object while it is being illuminated by the emitted light
Data Source
AI summary
Systems, methods, and computer-readable media are disclosed for a systems and methods for intra-shot dynamic LIDAR detector gain. One example method my include receiving first image data associated with a first image of an object illuminated at a first wavelength and captured by a camera at the first wavelength, the first image data including first pixel data for a first pixel of the first image and second pixel data for a second pixel of the first image. The example method may also include calculating a first reflectance value for the first pixel using the first pixel data. The example method may also include calculating a second reflectance value for the second pixel using the second pixel data. The example method may also include generating, using first reflectance value and the second reflectance value, a first reflectance distribution of the object.