Polarimetric camera

Patent metadata

Field	Value
Publication number	US-12469243-B2
Application number	US-202418435104-A
Country	US
Kind code	B2
Filing date	Feb 7, 2024
Priority date	Feb 7, 2023
Publication date	Nov 11, 2025
Grant date	Nov 11, 2025

Abstract

A polarization-sensitive encoder, a polarimetric camera, and a method for polarimetric imaging in which the encoder includes a two-dimensional (2D) polycrystalline photonic-crystal film with nanofiber, multi-scale, self-assembled structures.

First claim

What is claimed is:

1 . A polarimetric camera comprising:
a lens with a metagrating film adhered to the lens, the metagrating film including a two-dimensional (2D) photonic-crystal array with polyaniline hollow spheres (PANI-HS) nanostructures; a charged-coupled device (CCD) sensor configured to receive a speckle pattern from the lens with the metagrating film; and a computer system configured to process the speckle pattern received from the CCD sensor, and wherein points of polarized light from a scene are configured to be transmitted through the lens forming the speckle pattern on the CCD sensor.

2 . The polarimetric camera according to claim 1 , wherein the CCD sensor is a polarization-agnostic CCD sensor.

3 . The polarimetric camera according to claim 2 , wherein the computer system includes a computational algorithm configured to process the speckle pattern received from the polarization-agnostic CCD sensor.

4 . The polarimetric camera according to claim 3 , wherein the computational algorithm is a shallow neural networks algorithm.

5 . The polarimetric camera according to claim 1 , wherein the lens and the CCD sensor are not aligned with a scene that is being detected.

6 . The polarimetric camera according to claim 5 , wherein the lens and the CCD sensor are configured to form a non-coaxial or non-line-of-imaging system.

7 . The polarimetric camera according to claim 1 , wherein for a full-stokes imaging system, further comprising:
a single-shot image of the speckle pattern is captured from a partial segment of a Debye ring from the lens; and a speckle image from the single-shot image of the speckle pattern is input into a trained shallow neural networks (SSN) model for scene reconstruction.

8 . A method for polarimetric imaging comprising:
receiving a speckle pattern on a polarization-agnostic charged-coupled device (CCD) sensor from a lens having a metagrating film, the metagrating film including a two-dimensional (2D) photonic-crystal array with polyaniline hollow spheres (PANI-HS) nanostructures; and processing the speckle pattern received from the polarization-agnostic charged-coupled device (CCD) sensor with a computational algorithm to reconstruct a scene.

9 . The method for polarimetric imaging according to claim 8 , wherein the computational algorithm is a shallow neural networks algorithm.

10 . The method for polarimetric imaging according to claim 8 , further comprising:
transmitting points of polarized light from the scene through the lens and forming the speckle pattern received on the polarization-agnostic CCD sensor.

11 . The method for polarimetric imaging according to claim 8 , wherein for a full-stokes imaging system, further comprising:
capturing a single-shot image of the speckle pattern from a partial segment of a Debye ring from the lens; and inputting a speckle image from the single-shot image of the speckle pattern into a trained shallow neural networks (SSN) model to reconstruct the scene.

12 . A system for detecting an object comprising:
one or more markers configured to be placed or arranged on the object, the one or more markers being patterned with multi-scale features with meso-ordered, fractal statistics; an emitter configured to emit a beam of light towards the one or more markers on the object; and a receiver configured to detect a beam image of the emitted beam of light being reflected from the one or more markers on the object, and wherein the detected beam image from the beam of light is a code that identifies the object.

13 . The system according to claim 12 , wherein
the emitter and the receiver are part of a LiDAR (Laser Imaging and Distance Ranging) system, and LiDAR system includes a fisheye camera; and the marker is a LiDAR marker that identifies an object with a diffracted signature, which is received by a LIDAR sensor, the diffracted signature configured to identify the object.

14 . The system according to claim 13 , wherein
the object is one or more of a light pole, a traffic signal, a traffic sign, a barrier, and a building; and the fractal has one or more of a multi-scale “X” pattern, a multi-scale “+” pattern, a multiscale “bar-code” pattern, or an insect inspired pattern.

15 . The system according to claim 13 , wherein
the LiDAR system has a resolution of at least 2560×1920, a frequency of 10 Hz to 20 Hz, and a wavelength of 900 nm wavelength; the marker is at an angle of 0 to 45 degrees to the LiDAR system; the LiDAR system has a sensing area having a diameter of 20 cm or less; the object is one or more of a vertical and/or horizontal light or traffic pole, traffic symbols or traffic sign, a barrier, and a road surface, the road surface being an asphalt surface or concrete road surface with one or more markings; the emitter and the receiver are arranged on an autonomous vehicle, the autonomous vehicle being an automobile or a drone; and wherein the emitter and the receiver are used to track the object in real time.

16 . A method for detecting the object with the system according to claim 12 , the method comprising:
placing or arranging the one or more markers on the object, the one or more markers being patterned with the fractal with meso-ordered, multi-scale structures; emitting the beam of light towards the one or more markers on the object; and coherent imaging the beam image of the emitted beam of light being reflected from the one or more markers on the object.

17 . The method according to claim 16 , further comprising:
identifying the object based on the coherent imaging of the beam image of the emitted beam of light being reflected from the one or more markers, and wherein the fractal pattern is a meso-ordered, multi-scale distribution of features that identifies the object based on the polarized diffracted signature, and wherein the fractal has a “X” pattern, a “+” pattern, a “bar-code” pattern, or an insect inspired pattern.

18 . The method for polarimetric imaging according to claim 8 , wherein the polarization-agnostic CCD sensor is a CCD sensor with linear polarization filters, the method further comprises:
transmitting points of polarized light from the scene through the lens and forming the speckle pattern received on the CCD sensor with linear polarization filters.

Assignees

• Univ California

Inventors

• Vuong Luat Thanh
• Weng Xiaojing
• Perry Altai
• Feng Ji

Classifications

• G06V10/82

  using neural networks · CPC title

• G06T2207/30261

  Obstacle · CPC title

• G06T2207/30204

  Marker · CPC title

• G01S17/931 Primary

  of land vehicles · CPC title

• G01S17/74

  Systems using reradiation of electromagnetic waves other than radio waves, e.g. IFF, i.e. identification of friend or foe · CPC title