IP Library Granted Patent US 10,225,449
Granted Patent B2
US 10,225,449 · App. 15/511,772 · Granted Mar 5, 2019

Optical sensor systems and image processing methods for remote sensing

Inventor: Yun Zhang (Fredericton, CA)
Assignee: University of New Brunswick
H04N5/2258G01J3/28G01J3/2823G01J3/36G06T5/50H04N5/23232G01J2003/2826G06T2207/10036G06T2207/20221
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Quick Facts
Patent No.
US 10,225,449
App. No.
15/511,772
Granted
Mar 5, 2019
Kind
B2
Abstract

According to one embodiment, the present invention relates to (1) a sensor system configuration to record multi-level spatial and spectral information for creating high spatial resolution, large coverage, and high spectral resolution (hyperspectral) images, and (2) a multi-level spatial and spectral resolution sharpening method to create high spatial resolution, large coverage hyperspectral images.

Claims (93)

1. A method for producing a sharpened image comprising the steps of:

(1) obtaining image data defining a first image, the first image having a first spatial resolution and a first spectral resolution,

(2) obtaining image data defining a second image, the second image having a second spatial resolution and a second spectral resolution, the second spatial resolution being lower than the first spatial resolution and the second spectral resolution being higher than the first spectral resolution,

(3) obtaining image data defining a third image, the third image having a third spatial resolution and a third spectral resolution, the third spatial resolution being lower than the second spatial resolution and the third spectral resolution being higher than the second spectral resolution,

(4) fusing the image data of the second image and the third image to produce a fourth image, and

(5) fusing the image data of the first image and the fourth image to produce a fifth image, wherein the fifth image is a final sharpened image.

2. The method of claim 1 , where

the image data for the first image having been collected by one or more panchromatic sensors,

the image data for the second image having been collected by one or more multi-spectral sensors, and

the image data for the third image having been collected by one or more sensors selected from the group consisting of superspectral and hyperspectral sensors.

3. The method of claim 2 , where

all the sensors are either airborne based sensors or satellite-based sensors or terrestrial sensors.

4. The method of claim 1 , where

the first, second, and third images have a common overlapping area.

5. The method of claim 4 , where

the image data fused in steps (4) and (5) comprises image data defining all or a part of the common overlapping area.

6. The method of claim 1 , wherein:

(1) the first spatial resolution is a high spatial resolution, the first spectral resolution is a low spectral resolution, the first image being called a HR-Pan image;

(2) the second spatial resolution is a medium spatial resolution, the second spectral resolution is a medium spectral resolution, the second image being called a MR-MS image;

(3) the third spatial resolution is a low spatial resolution, the third spectral resolution is a high spectral resolution, the third image being called a LR-HS image;

(4) the fourth image is a sharpened MR-HS image; and

(5) the fifth image is a sharpened HR-HS image.

7. The method of claim 6 , wherein

the HR-Pan image has a spatial resolution of 1 m and 1 spectral band;

the MR-MS image has a spatial resolution of 3 m and 10 spectral bands; and

the LR-HS image has a spatial resolution of 9 m and 200 spectral bands.

8. The method of claim 6 , wherein

step (4) comprising fusing bands of the MR-MS image and bands of the LR-HS image to produce MR-HS bands, wherein the LR-HS bands being fused are located in the same or similar spectral range as the bands of the MR-MS image being fused, to produce fused MR-HS bands, and

step (5) comprising fusing the band of the HR-Pan image and the fused MR-HS bands, wherein the fused MR-HS bands are located in the same or similar spectral range as the band of the HR-Pan image.

9. The method of claim 6 , wherein

step (4) comprising fusing bands of the MR-MS image and bands of the LR-HS image to produce MR-HS bands, wherein the LR-HS bands being fused are not in the same or similar spectral range as the bands of the MR-MS image being fused, to produce fused MR-HS bands, and

step (5) comprising fusing the band of the HR-Pan image and the fused MR-HS bands, wherein the fused MR-HS bands are not located in the same or similar spectral range as the band of the HR-Pan image.

10. A method for producing a sharpened image comprising the steps of:

(1) obtaining image data defining a first image, the first image having a first spatial resolution and a first spectral resolution,

(2) obtaining image data defining a second image, the second image having a second spatial resolution and a second spectral resolution, the second spatial resolution being lower than the first spatial resolution and the second spectral resolution being higher than the first spectral resolution,

(3) obtaining image data defining a third image, the third image having a third spatial resolution and a third spectral resolution, the third spatial resolution being lower than the second spatial resolution and the third spectral resolution being higher than the second spectral resolution,

(4) obtaining image data defining a fourth image, the fourth image having a fourth spatial resolution and a fourth spectral resolution, the fourth spatial resolution being lower than the third spatial resolution and the fourth spectral resolution being higher than the third spectral resolution,

(5) fusing the image data of the third image and the fourth image to produce a fifth image,

(6) fusing the image data of the second image and the fifth image to produce a sixth image, and

(7) fusing the image data of the first image and the sixth image to produce a seventh image, wherein the seventh image is a final sharpened image.

11. The method of claim 10 , where

the image data for the first image having been collected by one or more panchromatic sensors,

the image data for the second image having been collected by one or more multi-spectral sensors,

the image data for the third image having been collected by one or more superspectral sensors, and

the image data for the fourth image having been collected by one or more hyperspectral sensors.

12. The method of claim 11 , where

all the sensors are either airborne based sensors or satellite-based sensors or terrestrial sensors.

13. The method of claim 10 , where

the first, second, third, and fourth images have a common overlapping area.

14. The method of claim 13 , where

the image data fused in steps (5)-(7) comprises image data defining all or a part of the common overlapping area.

15. A method for producing a sharpened image comprising:

(1) obtaining image data defining a high spatial resolution, low spectral resolution image, such image being called a HR-Pan (VNIR) image;

(2) obtaining image data defining a medium spatial resolution, medium spectral resolution, such image being called a MR-MS (VNIR) image;

(3) obtaining image data defining a low spatial resolution, medium spectral resolution image in another spectral range, such image being called a LR-MS (SWIR) image;

(4) obtaining medium spatial resolution Pan (VINR) image, such image being called MR-Pan (VNIR) image, from the HR-Pan (VNIR) image;

(5) obtaining low spatial resolution MS (VNIR) image, such image being called a LR-MS (VNIR) image, from the MR-MS (VNIR) image;

(6) fusing the LR-MS (SWIR) image and the MR-Pan (VNIR) image to produce a sharpened MR-MS (SWIR) image; and

(7) fusing the MR-MS (VNIR) image and the sharpened MR-MS (SWIR) image with the HR-Pan (VNIR) image to produce a sharpened HR-MS (VNIR) image and a HR-MS (SWIR) image.

16. The method of claim 15 , wherein

using at least one spectral band of the LR-MS (VNIR) image as reference in the step (6) to fuse the LR-MS (SWIR) image and the MR-Pan (VNIR) image, to produce a sharpened MR-MS (SWIR) image.

17. The method of claim 15 , wherein

using at least one spectral band of the MR-MS (VNIR) image as reference in the step (7) to fuse the MR-MS (VNIR) image and the MR-MS (SWIR) image with the HR-Pan (VNIR) image, to produce a sharpened HR-MS (VNIR) image and HR-MS (SWIR) image.

18. An image sensor configuration for airborne or satellite-based or terrestrial imagery, the sensor configuration comprising:

a Pan sensor;

a MS sensor; and

a HS sensor,

wherein the Pan sensor is configured to obtain image data defining a high spatial resolution and low spectral resolution image;

the MS sensor is configured to obtain image data defining a medium spatial resolution and medium spectral resolution image;

the HS sensor is configured to obtain image data defining a low spatial resolution and high spectral resolution image, and

wherein, the sensors cover have the same ground coverage.

19. The image sensor configuration of claim 18 , further comprising:

a SS sensor configured to obtain image data defining a spatial resolution between those of the MS sensor and the HS sensor, and a spectral resolution between those of the MS sensor and the HS sensor.

20. An image sensor configuration for airborne or satellite-based or terrestrial imagery, the sensor configuration comprising:

first, second and third image sensors, wherein

the first image sensor having a first spatial resolution and a first spectral resolution,

the second image sensor having a second spatial resolution and a second spectral resolution, the second spatial resolution being lower than the first spatial resolution and the second spectral resolution being higher than the first spectral resolution, and

the third image sensor having a third spatial resolution and a third spectral resolution, the third spatial resolution being lower than the second spatial resolution and the third spectral resolution being higher than the second spectral resolution.

21. A method for producing a sharpened image comprising:

obtaining image data defining a high spatial resolution MS image,

obtaining image data defining a low spatial resolution MS,

simulating a high spatial resolution Pan image from the high spatial resolution MS image by combining all the MS bands of the high spatial resolution MS image into one band, and

fusing the simulated high spatial resolution Pan image with the low spatial resolution MS image to generate a high spatial resolution MS image that has the same bandwidth as the low spatial resolution MS image.

22. The method of claim 21 , wherein the spectral ranges of the high spatial resolution MS image is the same as or similar to that of the low spatial resolution MS image.

23. The method of claim 21 further comprising:

reducing the spatial resolution of the high spatial resolution MS image to that of the low spatial resolution MS image through pixel binning to simulate a low spatial resolution MS image, and

in fusing the simulated high spatial resolution Pan image with the low spatial resolution MS image, using at least one spectral band of the simulated low spatial resolution MS image as a reference to generate the high spatial resolution MS image that has the same bandwidth as the low spatial resolution MS image.

24. The method of claim 23 wherein the spectral range of the high spatial resolution MS image is not the same as or similar to that of the low spatial resolution MS image.

25. A method for producing a sharpened image comprising:

obtaining image data defining a high spatial resolution Pan image (HR-Pan image);

obtaining a low spatial resolution MS image having a narrower cumulative spectral bandwidth (LR-MS-N image) than that of the HR-Pan image;

simulating a low spatial resolution MS band (S-LR-MS band) from the HR-Pan image and the LR-MS-N image to fill the spectral gap between the HR-Pan image and the LR-MS-N image; and,

fusing the HR-Pan image with the LR-MS-N image and S-LR-MS band to obtain a high spatial resolution MS image.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 19, 2023
From: TERRIS EARTH INTELLIGENCE INC.
To: THE UNIVERSITY OF NEW BRUNSWICK
Reel/Frame 065275/0659 →
CHANGE OF NAME Recorded Apr 6, 2022
From: 3D PLANETA INC.
To: TERRIS EARTH INTELLIGENCE INC.
Reel/Frame 059618/0091 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 28, 2021
From: THE UNIVERSITY OF NEW BRUNSWICK
To: 3D PLANETA INC.
Reel/Frame 056074/0934 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 20, 2017
From: ZHANG, YUN
To: UNIVERSITY OF NEW BRUNSWICK
Reel/Frame 042758/0781 →
Continuity (2)
Provisional Application 62051105 · Sep 16, 2014
Related Publication 20170251134A1 · Aug 31, 2017
Cited By (1)
US 12,664,611