Method and apparatus for extracting mountain landscape buildings based on high-resolution remote sensing images

Patent metadata

Field	Value
Publication number	US-11615615-B2
Application number	US-202117153967-A
Country	US
Kind code	B2
Filing date	Jan 21, 2021
Priority date	Jun 25, 2019
Publication date	Mar 28, 2023
Grant date	Mar 28, 2023

Abstract

The present invention discloses a method and an apparatus for extracting mountain landscape buildings based on high-resolution remote sensing images. The method comprises: segmenting a remote sensing image, and extracting non-vegetation areas from the remote sensing image by using NDVI; segmenting the non-vegetation areas, and extracting building areas by using NDBI; segmenting the building areas again, and calculating a normalized difference build shadow index NSBI of each patch; calculating NSBI separator of each patch in the non-vegetation areas and setting a separator threshold, and extracting landscape building areas based on the threshold. In the present invention, by introducing a near infrared band in the remote sensing image spectrum, in which there is a significant difference between shadows and non-shadows, the influence of large shadow areas in mountainous shady areas in the remote sensing image on the result of extraction is reduced.

First claim

The invention claimed is:

1. A method for extracting mountain landscapes buildings based on high-resolution remote sensing images, comprising the following steps:
S 1 : segmenting a remote sensing image into patches of a first scale by using a first scale parameter A 1 , calculating a normalized difference vegetation index NDVI of each patch, and extracting the segmented patches with NDVI greater than a first threshold T 1 as vegetation areas, while other patches as non-vegetation areas;
S 2 : segmenting the non-vegetation areas by using a second scale parameter A 2 to obtain patches of a second scale, calculating a normalized difference buildup index NDBI of each patch, and judging the patches of the second scale with NDBI greater than a second threshold T 2 as building areas, while regarding other patches as non-building areas;
S 3 : segmenting the non-vegetation areas by using a third scale parameter A 3 to obtain patches of a third scale, and calculating a normalized difference build shadow index NSBI of each patch;
S 4 : calculating a normalized difference build shadow index separator S x (NSBI) of each patch according to the NSBI, and extracting the areas with a separator greater than a third threshold T 3 as landscape buildings,
wherein the normalized difference build shadow index separator Sx (NSBI) is calculated with the following formula:

S
x

(
NSBI
)

=

∑

x
i

∈

n
⁡
(
x
)

,

m

x
i

(
l
)

<

m
x

(
l
)

B
⁡
(

x
,

x
i

)

⁢

(

m
x

(
NSBI
)

-

m

x
i

(
NSBI
)

)

∑

x
i

∈

n
⁡
(
x
)

B
⁡
(

x
,

x
i

)

wherein, x represents the current calculated patch, n(x) represents a set of all patches adjacent to the current calculated patch, B(x, x i ) is the length of a common side of the current calculated patch x and the adjacent patch x i , and m x (NSBI) represents the NSBI value of the calculated patch x;
wherein the first scale parameter A 1 >the second scale parameter A 2 >the third scale parameter A 3 .

2. The method for extracting mountain landscape buildings based on high-resolution remote sensing image according to claim 1 , wherein the method uses the Multiresolution Segmentation algorithm or Hyper-pixel Segmentation algorithm to segment the image.

3. The method for extracting mountain landscape buildings based on high-resolution remote sensing image according to claim 1 , wherein the normalized difference vegetation index NDVI in the step S 1 is calculated with the following formula:

NDVI
=

NIR
-
R

NIR
+
R

wherein, NIR is the mean valve of the near infrared band of the current calculated patch, and R is the mean valve of the red band of the current calculated patch.

4. The method for extracting mountain landscape buildings based on high-resolution remote sensing image according to claim 1 , wherein the normalized difference build shadow index NSBI in the step S 2 is calculated with the following formula:

NDBI
=

NIR
+
R

NIR
-
R

wherein, NIR is the mean valve of the near infrared band of the current calculated patch, and R is the mean valve of the red band of the current calculated patch.

5. The method for extracting mountain landscape buildings based on high-resolution remote sensing image according to claim 1 , wherein the normalized difference build shadow index NSBI of each patch is calculated with the following formula in the step S 3 :

NSBI
=

NDBI
*
NIR

=

(

NIR
+

Assignees

• Univ Southeast

Inventors

• Li Zhe
• He Yukun
• Cheng Yuning
• Zhou Xiang
• Zhao Kaiyu
• Han Xiao
• Chen Feifei
• Song Shuang
• Lu Xinyi
• Lin Xiaoshan

Classifications

• G06V20/188 Primary

  Vegetation · CPC title

• G06V10/28

  Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns · CPC title

• G06T2207/10036

  Multispectral image; Hyperspectral image · CPC title

• G06V20/194

  using hyperspectral data, i.e. more or other wavelengths than RGB · CPC title

• G06T2207/30188

  Vegetation; Agriculture · CPC title