IP Library Granted Patent US 12,483,801
Granted Patent B2
US 12,483,801 · App. 17/940,864 · Granted Nov 25, 2025

Image sensor, method for operating an image sensor, method for manufacturing an image sensor, and stationary device or vehicle or drone having an image sensor

Inventors: Dietrich Dumler (Munich, DE); Franz Wenninger (Munich, DE); Christoph Kutter (Munich, DE)
Assignee: Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V.
H04N25/11B60R1/24G02B5/201G02B5/3025H04N25/131H04N25/135B64C39/024B64U2101/31
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,483,801
App. No.
17/940,864
Granted
Nov 25, 2025
Kind
B2
Abstract

Embodiments of the invention provide an image sensor image sensor including an image sensor structure. The image sensor structure includes a multitude of image elements arranged in a grid-shaped manner in a first direction and in a second direction orthogonal to the first direction. An image element of the multitude of image elements includes a plurality of filter elements spatially arranged side by side. The plurality of filter elements includes at least one color filter and at least one additional filter from a filter group. The filter group includes a first absorption filter with a first optical bandwidth, a second absorption filter with a second optical bandwidth different from the first optical bandwidth, a first polarization filter with a first polarization characteristic, a second polarization filter with a second polarization characteristic different from the first polarization characteristic, and a filter element without absorption effect or polarization effect.

Claims (44)

1 . Image sensor comprising:

an image sensor structure comprising a multitude of image elements arranged in a grid-shaped manner in a first direction and in a second direction orthogonal to the first direction,

wherein each image element of the multitude of image elements comprises a first stack of filter elements and a second stack of filter elements, wherein the second stack of filter elements is arranged side by side with the first stack of filter elements in the first direction,

wherein each one of the first stack of filter elements and the second stack of filter elements comprises a plurality of filter elements spatially arranged side by side,

wherein the plurality of filter elements of the first stack of filter elements and the plurality of filter elements of the second stack of filter elements are extended in a flat structure in which filter elements of the first stack of filter elements and filter elements of the second stack of filter elements are arranged in one line or in two lines,

wherein the first stack of filter elements comprises at least a first color filter, a second color filter, and a third color filter, wherein the third color filter is different from the first color filter and the second color filter, and wherein the first color filter is different from the second color filter,

wherein the second stack of filter elements comprises a first absorption filter with a first optical bandwidth, wherein the first optical bandwidth is selected from a spectral range of between 900 nm and 1200 nm, a second absorption filter with a second optical bandwidth, wherein the second optical bandwidth is selected from a spectral range of between 400 nm and 900 nm and is different from the first optical bandwidth, a first polarization filter with a first polarization characteristic, and a second polarization filter with a second polarization characteristic different from the first polarization characteristic,

wherein the first absorption filter and the second absorption filter have optical bandwidths in which water has different absorption rates in order to detect water on a road surface, and

wherein the first polarization filter with a first polarization characteristic, and the second polarization filter with the second polarization characteristic have different polarization characteristics in order to differentiate between water, snow, and black ice.

2 . Vehicle, comprising:

a vehicle front side directed towards a road surface in a driving direction of the vehicle and extending upwards with respect to the road surface; and

an image sensor according to claim 1 , attached at the vehicle front side in an upper area of the vehicle front side and oriented in the driving direction.

3 . The vehicle according to claim 2 , wherein the image sensor is arranged such that the first direction of the image sensor structure is arranged transversally to the driving direction, and such that the second direction of the image sensor structure is arranged longitudinally to the driving direction, wherein the second stack is placed adjacent to the first stack in the first direction being transversally to the driving direction.

4 . Stationary device, comprising:

a front side directed towards a road surface in a driving direction of a vehicle and extending upwards with respect to the road surface; and

an image sensor according to claim 1 , attached at the front side in an upper area of the front side and oriented to the driving direction.

5 . The stationary device according to claim 4 , wherein the image sensor is arranged such that the first direction of the image sensor structure is arranged transversally to the driving direction, and such that the second direction of the image sensor structure is arranged longitudinally to the driving direction, wherein the second stack is placed adjacent to the first stack in the first direction being transversally to the driving direction.

6 . The stationary device according to claim 4 , wherein the stationary device further comprises a processor, and a display,

wherein the processor is configured to estimate a state of the road surface on the basis of a sensor recording of the image sensor; and

wherein the display is configured to inform a driver of the vehicle about the state of the road surface, or to inform a driver of the vehicle about a dangerous state of the road surface.

7 . The stationary device according to claim 4 , wherein the stationary device is configured to inform a remote server about a state of the road surface, or to inform a remote server about a dangerous state of the road surface.

8 . Drone with an image sensor according to claim 1 , wherein the image sensor is configured to be oriented in a moving direction relative to a road surface.

9 . The drone according to claim 8 , wherein the image sensor is arranged such that the first direction of the image sensor structure is arranged transversally to the moving direction, and such that the second direction of the image sensor structure is arranged longitudinally to the moving direction, wherein the second stack is placed adjacent to the first stack in the first direction being transversally to the moving direction.

10 . The drone according to claim 8 , wherein the drone is configured to inform a remote server about a state of the road surface, or to inform a remote server about a dangerous state of the road surface.

11 . The image sensor according to claim 1 , wherein the first stack of filter elements comprises, as the first color filter, a red color filter, as the second color filter, a green color filter, and, as the third color filter, a blue color filter.

12 . The image sensor according to claim 1 , wherein the second optical bandwidth of the second absorption filter comprises, at a half-power bandwidth, a value of between 820 nm and 870 nm, and wherein the first optical bandwidth of the first absorption filter comprises, at the half-power bandwidth, a value of between 920 nm and 970 nm.

13 . The image sensor according to claim 1 ,

wherein the first stack of filter elements comprises: a green filter, a blue filter placed adjacent to the green filter in the first direction, a red filter adjacent to the green filter in the second direction, and another green filter adjacent to the red filter in the first direction and adjacent to the blue filter in the second direction, and,

wherein the second stack comprises: the first absorption filter, the second absorption filter, the first polarization filter and the second polarization filter, wherein the second absorption filter is placed adjacent to the first absorption filter in the first direction, the first polarization filter is placed adjacent to the first absorption filter in the second direction, and the second polarization filter is placed adjacent to the first polarization filter in the first direction and adjacent to the first second absorption filter in the second direction.

14 . The image sensor according to claim 13 , wherein the first stack and the second stack are arranged in two lines side by side in the first direction,

wherein the second absorption filter of the second stack is arranged adjacent to the blue filter of the first stack in the first direction, and

wherein the first polarization filter of the second stack is placed adjacent to the further green filter of the first stack in the first direction.

15 . The image sensor according to claim 1 , wherein the polarization characteristic of the first polarization filter and the polarization characteristic of the second polarization filter are configured to be shifted by 90° with respect to each other.

16 . The image sensor according to claim 1 , wherein the first stack of filter elements and the second stack of filter elements are arranged in two lines side by side in the first direction.

17 . The image sensor according to claim 1 , wherein the image sensor is configured to selectively read out each image sensor portion associated to each individual filter element of the first stack of filter elements and the second stack of filter elements in the image element.

18 . Method for operating an image sensor with an image element structure comprising a multitude of image elements arranged in a grid-shaped manner in a first direction and in a second direction orthogonal to the first direction, wherein each image element of the multitude of image elements comprises a first stack of filter elements and a second stack of filter elements, arranged side by side with the first stack of filter elements in the first direction, wherein each one of the first stack of filter elements and the second stack of filter elements comprises a plurality of filter elements spatially arranged side by side, wherein the plurality of filter elements of the first stack of filter elements and the plurality of filter elements of the second stack of filter elements are extended in a flat structure in which filter elements of the first stack of filter elements and filter elements of the second stack of filter elements are arranged in one line or in two lines, wherein the first stack of filter elements comprises at least a first color filter, a second color filter, and a third color filter, wherein the third color filter is different from the first color filter and the second color filter, and wherein the first color filter is different from the second color filter, wherein the second stack of filter elements comprises a first absorption filter with a first optical bandwidth, wherein the first optical bandwidth is selected from a spectral range of between 900 nm and 1200 nm, a second absorption filter with a second optical bandwidth, wherein the second optical bandwidth is selected from a spectral range of between 400 nm and 900 nm and is different from the first optical bandwidth, a first polarization filter with a first polarization characteristic, and a second polarization filter with a second polarization characteristic different from the first polarization characteristic, the method comprising:

reading out a first light-sensitive area associated to the first and second color filters of the first stack of filter elements; and

reading out a second light-sensitive area associated to the first absorption filter, the second absorption filter, the first polarization filter, and the second polarization filter,

wherein the first absorption filter and the second absorption filter have optical bandwidths in which water has different absorption rates in order to detect water on a road surface, and

wherein the first polarization filter with a first polarization characteristic, and the second polarization filter with the second polarization characteristic have different polarization characteristics in order to differentiate between water, snow, and black ice.

19 . Method for manufacturing an image sensor with an image element structure comprising a multitude of image elements arranged in a grid-shaped manner in a first direction and in a second direction orthogonal to the first direction, the method comprising:

configuring the image elements of the multitude of image elements such that each image element of the multitude of image elements comprises a first stack of filter elements and a second stack of filter elements, wherein the second stack of filter elements is arranged side by side with the first stack of filter elements in the first direction, wherein each one of the first stack of filter elements and the second stack of filter elements comprises a plurality of filter elements spatially arranged side by side, wherein the plurality of filter elements of the first stack of filter elements and the plurality of filter elements of the second stack of filter elements are extended in a flat structure in which filter elements of the first stack of filter elements and filter elements of the stack of filter elements are arranged in one line or in two lines, wherein the first stack of filter elements comprises at least a first color filter, a second color filter, and a third color filter, wherein the third color filter is different from the first color filter and the second color filter, and wherein the first color filter is different from the second color filter, wherein the second stack of filter elements comprises a first absorption filter with a first optical bandwidth, wherein the first optical bandwidth is selected from a spectral range of between 900 nm and 1200 nm, a second absorption filter with a second optical bandwidth, wherein the second optical bandwidth is selected from a spectral range of between 400 nm and 900 nm and is different from the first optical bandwidth, a first polarization filter with a first polarization characteristic, and a second polarization filter with a second polarization characteristic different from the first polarization characteristic,

wherein the first absorption filter and the second absorption filter have optical bandwidths in which water has different absorption rates in order to detect water on a road surface, and

wherein the first polarization filter with a first polarization characteristic, and the second polarization filter with the second polarization characteristic have different polarization characteristics in order to differentiate between water, snow, and black ice.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 22, 2022
From: DUMLER, DIETRICH; WENNINGER, FRANK; KUTTER, CHRISTOPH
To: FRAUNHOFER-GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
Reel/Frame 062190/0760 →
Priority Claims (2)
DE 102021210050.3 · Sep 10, 2021 · national
DE 10 2022 201 523.1 · Feb 14, 2022 · national
Continuity (1)
Related Publication 20230081017A1 · Mar 16, 2023
References Cited (72)
US 5557261A · Barbour · 1996 [cited by examiner]
US 8411146B2 · Twede · 2013 [cited by applicant]
US 10823562B1 · Carnahan · 2020 [cited by examiner]
US 11520018B2 · Baumgartner et al. · 2022 [cited by applicant]
US 20080129541A1 · Lu · 2008 [cited by examiner]
US 20100295947A1 · Boulanger · 2010 [cited by applicant]
US 20110149076A1 · Capello et al. · 2011 [cited by applicant]
US 20130144490A1 · Lord · 2013 [cited by examiner]
US 20140084404A1 · Fukunaga · 2014 [cited by examiner]
US 20150070528A1 · Kikuchi · 2015 [cited by examiner]
US 20150221691A1 · Watanabe · 2015 [cited by applicant]
US 20150339919A1 · Barnett · 2015 [cited by examiner]
US 20150371095A1 · Hartmann et al. · 2015 [cited by applicant]
US 20160069743A1 · McQuilkin · 2016 [cited by examiner]
US 20160200161A1 · Van Den Bossche et al. · 2016 [cited by applicant]
US 20160358332A1 · Watanabe · 2016 [cited by examiner]
US 20170124402A1 · Tanaka et al. · 2017 [cited by applicant]
US 20180027191A2 · Grauer · 2018 [cited by examiner]
US 20180302564A1 · Liu et al. · 2018 [cited by applicant]
US 20190188495A1 · Zhao et al. · 2019 [cited by applicant]
US 20190188827A1 · Mitani · 2019 [cited by examiner]
US 20190260974A1 · Kaizu et al. · 2019 [cited by applicant]
US 20190306471A1 · Otsuki · 2019 [cited by applicant]
US 20190378257A1 · Fan · 2019 [cited by examiner]
US 20200023995A1 · Song · 2020 [cited by examiner]
US 20200260055A1 · Choi · 2020 [cited by examiner]
US 20200280707A1 · Briggs et al. · 2020 [cited by applicant]
US 20200286371A1 · Yuasa · 2020 [cited by examiner]
US 20200317202A1 · Staudacher et al. · 2020 [cited by applicant]
US 20200350353A1 · Kurita · 2020 [cited by examiner]
US 20210065565A1 · Dow · 2021 [cited by examiner]
US 20210118931A1 · Matsunuma et al. · 2021 [cited by applicant]
US 20210241224A1 · Taniguchi · 2021 [cited by examiner]
US 20210297638A1 · Sugiyama · 2021 [cited by examiner]
US 20220107266A1 · Baumgartner et al. · 2022 [cited by applicant]
US 20220180643A1 · Retterath · 2022 [cited by examiner]
US 20220185313A1 · Wang et al. · 2022 [cited by applicant]
US 20220196545A1 · Imawaka et al. · 2022 [cited by applicant]
US 20230049577A1 · Gruev · 2023 [cited by examiner]
US 20230314567A1 · Dekel · 2023 [cited by examiner]
US 20240155261A1 · Iseri · 2024 [cited by examiner]
CN 103703769A · 2014 [cited by applicant]
CN 207165573U · 2018 [cited by applicant]
CN 110546950A · 2019 [cited by applicant]
CN 113257000A · 2021 [cited by applicant]
DE 102009036595A1 · 2011 [cited by applicant]
DE 102012110092A1 · 2014 [cited by applicant]
DE 102012110094A1 · 2014 [cited by applicant]
DE 102014224857A1 · 2016 [cited by applicant]
DE 102018132525A1 · 2019 [cited by applicant]
DE 112017005244T5 · 2019 [cited by applicant]
DE 102019205903A1 · 2020 [cited by applicant]
DE 112019003967T5 · 2021 [cited by applicant]
EP 2375755B1 · 2013 [cited by applicant]
EP 3133646A2 · 2017 [cited by applicant]
JP 2007232652A · 2007 [cited by applicant]
JP 2017083352A · 2017 [cited by applicant]
JP 6161007B2 · 2017 [cited by applicant]
JP 2018036314A · 2018 [cited by applicant]
JP 2018098641A · 2018 [cited by applicant]
JP 2020180924A · 2020 [cited by applicant]
WO 2010052593A1 · 2010 [cited by applicant]
WO 2011015196A1 · 2011 [cited by applicant]
WO 2013018743A1 · 2013 [cited by applicant]
WO 2013173911A1 · 2013 [cited by applicant]
WO 2014063701A1 · 2014 [cited by applicant]
WO 2020198134A1 · 2020 [cited by applicant]
Huber, Daniel F, et al., “A Spectro-polarimetric Imager for Intelligent Transportation Systems”, Intelligent Transportation Systems, Oct. 17, 1997 pp. 94-102, XP055101934, Oct. 17, 1997, pp. 94-102. [cited by applicant]
Misener, James A, “UC Berkeley Working Papers Title Investigation Of An Optical Method To Determine The Presence Of Ice On Road Surfaces”, California Path Program, Jan. 1, 1998 pp. 1-20, XP093017038, Jan. 1, 1998, pp. 1… [cited by applicant]
Jonsson, Patrik, et al., “[Uploaded in 2 parts] Road Surface Status Classification Using Spectral Analysis of NIR Camera Images”, IEEE Sensors Journal, vol. 15, No. 3, pp. 1641-1656, pp. 1641-1648. [cited by applicant]
Jonsson, Patrik, et al., “Road Surface Status Classification Using Spectral Analysis of NIR Camera Images (Uploaded in 3 parts)”, In: IEEE Sensors Journal, vol. 15, No. 3, 2015, S. 1641-1656. [cited by applicant]
Wu, Yan, “A Survey of Vision-Based Road Parameter Estimating Methods”, Oct. 5, 2020 (Oct. 5, 2020), 20201005, pp. 314-325, XP047567286. [cited by applicant]