IP Library Granted Patent US 9,686,478
Granted Patent B2
US 9,686,478 · App. 14/945,927 · Granted Jun 20, 2017

Generating high-dynamic range images using multiple filters

Inventors: Mark Allen Robertson (Cupertino, CA); Ken James Kryda (Sunnyvale, CA)
Assignee: Google Inc.
H04N5/2355H04N5/2353
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Quick Facts
Patent No.
US 9,686,478
App. No.
14/945,927
Granted
Jun 20, 2017
Kind
B2
Abstract

Systems and methods are provided for generating high-dynamic range images. In particular, a signal-to-noise (SNR) ratio objective associated with an imaging platform configured to capture one or more images of a region of interest using an image sensor having a first portion and a second portion can be determined. The SNR objective can specify a desired SNR response as a function of a brightness of the region of interest. A first integration time and a second integration time can then be determined based at least in part on the SNR objective. Data indicative of a plurality of image frames can then be obtained. Each image frame is captured by exposing the first portion of the image sensor for the first integration time and exposing the second portion of the image sensor for the second integration time.

Claims (34)

1. A computer-implemented method of creating high-dynamic range images, the method comprising:

determining, by one or more computing devices, a signal-to-noise ratio objective associated with an imaging platform configured to capture one or more images of a region of interest using an image sensor having a first portion and a second portion, the signal-to-noise ratio objective specifying a desired signal-to-noise ratio response as a function of a brightness of the region of interest;

determining, by the one or more computing devices, a first integration time associated with the first portion of the image sensor and a second integration time associated with the second portion of the image sensor, the first and second integration times being determined based at least in part on the signal-to-noise ratio objective;

obtaining, by the one or more computing devices, data indicative of a plurality of image frames, each depicting at least a portion of the region of interest, wherein each image frame is captured at least in part by exposing the first portion of the image sensor for the first integration time and exposing the second portion of the image sensor for the second integration time; and

generating, by the one or more computing devices, a high-dynamic range image of at least a portion of the region of interest based at least in part on the plurality of image frames.

2. The computer-implemented method of claim 1 , wherein the first integration time is different than the second integration time.

3. The computer-implemented method of claim 1 , wherein the first portion of the imaging sensor corresponds to a panchromatic block.

4. The computer-implemented method of claim 3 , wherein the second portion of the imaging sensor corresponds to a multispectral block.

5. The computer-implemented method of claim 4 , wherein the multispectral block comprises a plurality of spectral filters, each configured to transmit light within a range of wavelengths.

6. The computer-implemented method of claim 1 , wherein the second portion of the imaging sensor corresponds to a neural density filter.

7. The computer-implemented method of claim 1 , wherein the first portion of the imaging sensor comprises one or more first filters disposed between the first portion of the imaging sensor and the region of interest, and the second portion of the imaging sensor comprises one or more second filters disposed between the second portion of the imaging sensor and the region of interest.

8. The computer-implemented method of claim 1 , wherein the imaging sensor comprises a first photosensor and a second photosensor, and wherein the first portion of the imaging sensor corresponds to the first photosensor and the second portion of the imaging sensor corresponds to the second photosensor.

9. The computer-implemented method of claim 1 , wherein the first integration time and the second integration time are determined to shape the signal-to-noise ratio response in accordance with the signal-to-noise ratio objective.

10. The computer-implemented method of claim 1 , wherein each image frame of the plurality of image frames is captured by exposing the first portion of the imaging sensor and the second portion of the imaging sensor in a serial manner.

11. The computer-implemented method of claim 1 , wherein each image frame of the plurality of image frames is captured by simultaneously exposing the first portion of the imaging sensor and the second portion of the imaging sensor.

12. A computing system, comprising:

one or more processors; and

one or more memory devices, the one or more memory devices storing computer-readable instructions that when executed by the one or more processors cause the one or more processors to perform operations, the operations comprising:

determining a signal-to-noise ratio objective associated with an imaging platform configured to capture one or more images of a region of interest using an image sensor having a first portion and a second portion, the signal-to-noise ratio objective specifying a desired signal-to-noise ratio curve as a function of a brightness of the region of interest;

determining a first integration time associated with the first portion of the image sensor and a second integration time associated with the second portion of the image sensor, the first and second integration times being determined based at least in part on the signal-to-noise ratio objective;

obtaining data indicative of a plurality of image frames, each depicting at least a portion of the region of interest, wherein each image frame is captured at least in part by exposing the first portion of the image sensor for the first integration time and exposing the second portion of the image sensor for the second integration time; and

generating a high-dynamic range image of at least a portion of the region of interest based at least in part on the plurality of image frames.

13. The computing system of claim 12 , wherein the first integration time and the second integration time are determined to shape the signal-to-noise ratio response in accordance with the signal-to-noise ratio objective.

14. The computing system of claim 12 , wherein the first integration time and the second integration time are determined as part of one or more exposure profiles associated with the imaging platform, the one or more exposure profiles specifying an integration time to be used in capturing each image frame of the plurality of image frames.

15. The computing system of claim 12 , wherein the first portion of the imaging sensor corresponds to a multispectral block.

16. The computing system of claim 12 , wherein the first portion of the imaging sensor corresponds to a neural density filter.

17. One or more tangible, non-transitory computer-readable media storing computer-readable instructions that when executed by one or more processors cause the one or more processors to perform operations, the operations comprising:

determining a signal-to-noise ratio objective associated with an imaging platform configured to capture one or more images of a region of interest using an image sensor having a first portion and a second portion, the signal-to-noise ratio objective specifying a desired signal-to-noise ratio curve as a function of a brightness of the region of interest;

determining a first integration time associated with the first portion of the image sensor and a second integration time associated with the second portion of the image sensor, the first and second integration times being determined based at least in part on the signal-to-noise ratio objective;

obtaining data indicative of a plurality of image frames, each depicting at least a portion of the region of interest, wherein each image frame is captured at least in part by exposing the first portion of the image sensor for the first integration time and exposing the second portion of the image sensor for the second integration time; and

generating a high-dynamic range image of at least a portion of the region of interest based at least in part on the plurality of image frames.

18. The one or more tangible, non-transitory computer-readable media of claim 17 , wherein the first portion of the imaging sensor comprises one or more first filters disposed between the first portion of the imaging sensor and the region of interest, and the second portion of the imaging sensor comprises one or more second filters disposed between the second portion of the imaging sensor and the region of interest.

19. The one or more tangible, non-transitory computer-readable media of claim 17 , wherein the imaging sensor comprises a first photosensor and a second photosensor, and wherein the first portion of the imaging sensor corresponds to the first photosensor and the second portion of the imaging sensor corresponds to the second photosensor.

20. The one or more tangible, non-transitory computer-readable media of claim 17 , wherein the first integration time and the second integration time are determined to shape the signal-to-noise ratio response in accordance with the signal-to-noise ratio objective.

Assignments (10)
CORRECTIVE ASSIGNMENT TO CORRECT THE THE REMOVAL OF THE INCORRECTLY RECORDED APPLICATION NUMBERS 14/149802 AND 15/419313 PREVIOUSLY RECORDED AT REEL: 44144 FRAME: 1. ASSIGNOR(S) HEREBY CONFIRMS THE CHANGE OF NAME. Recorded Mar 4, 2024
From: GOOGLE INC.
To: GOOGLE LLC
Reel/Frame 068092/0502 →
MERGER AND CHANGE OF NAME Recorded May 5, 2022
From: PLANET LABS INC.; PLANET LABS PBC
To: PLANET LABS PBC
Reel/Frame 059857/0587 →
RELEASE OF SECURITY INTEREST Recorded Dec 10, 2021
From: SILICON VALLEY BANK
To: PLANET LABS INC.; TERRA BELLA TECHNOLOGIES INC.; PL FOREIGN HOLDCO, INC.
Reel/Frame 058359/0501 →
INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Jun 21, 2019
From: PLANET LABS INC.; PL INTERMEDIATE TB, INC.; PLANET LABS TB, INC.; TERRA BELLA TECHNOLOGIES INC.; PLANET LABS LLC; PL FOREIGN HOLDCO, INC.
To: SILICON VALLEY BANK
Reel/Frame 049558/0515 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 30, 2017
From: PLANET LABS TB, INC.
To: PLANET LABS, INC.
Reel/Frame 044260/0159 →
CHANGE OF NAME Recorded Oct 6, 2017
From: GOOGLE INC.
To: GOOGLE LLC
Reel/Frame 044144/0001 →
CORRECTIVE ASSIGNMENT TO CORRECT THE INCORRECT SERIAL NO. 15/061,851 PREVIOUSLY RECORDED AT REEL: 043277 FRAME: 0669. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Aug 18, 2017
From: GOOGLE INC.
To: PLANET LABS TB, INC.
Reel/Frame 043661/0060 →
CORRECTIVE ASSIGNMENT TO CORRECT THE NAME OF THE ASSIGNEE PREVIOUSLY RECORDED AT REEL: 043277 FRAME: 0669. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Aug 17, 2017
From: GOOGLE INC.
To: PLANET LABS TB, INC.
Reel/Frame 043409/0837 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 14, 2017
From: GOOGLE INC.
To: PLANT LABS TB, INC.
Reel/Frame 043277/0669 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 19, 2015
From: ROBERTSON, MARK ALLEN; KRYDA, KEN JAMES
To: GOOGLE INC.
Reel/Frame 037089/0483 →
Continuity (1)
Related Publication 20170150029A1 · May 25, 2017