Zonal underground structure detection method based on sun shadow compensation

Patent metadata

Field	Value
Publication number	US-2016371841-A1
Application number	US-201515106686-A
Country	US
Kind code	A1
Filing date	Feb 10, 2015
Priority date	Dec 30, 2014
Publication date	Dec 22, 2016
Grant date	—

Abstract

A zonal underground structure detection method based on sun shadow compensation is provided, which belongs to the crossing field of remote sensing technology, physical geography and pattern recognition, and is used to carry out compensation processing after a shadow is detected, to improve the identification rate of zonal underground structure detection and reduce the false alarm rate. The present invention comprises steps of acquiring DEM terrain data of a designated area, acquiring an image shadow position by using DEM, a solar altitude angle and a solar azimuth angle, processing and compensating a shadow area, and detecting a zonal underground structure after the shadow area is corrected. In the present invention, the acquired DEM terrain data is used to detect the shadow in the designated area; and the detected shadow area is processed and compensated, to reduce influence of the shadow area on zonal underground structure detection; finally, the zonal underground structure is detected by using a remote sensing image after shadow compensation, so that the accuracy of zonal underground structure detection is improved and the false alarm rate is reduced compared with zonal underground structure detection using a remote sensing image without shadow compensation processing.

First claim

1 . A zonal underground structure detection method based on sun shadow compensation, wherein the method comprises steps of:
(1) determining latitude and longitude information of an area to be detected according to a geographic position of the area to be detected, then calculating a latitude step size and a longitude step size according to the resolution of an infrared remote sensing image, acquiring altitude information of the area to be detected according to the latitude and longitude information and the latitude step size and longitude step size of the area to be detected, and finally correcting the obtained altitude information; (2) rotating the corrected altitude image by using solar azimuth angle information, calculating a ratio of a mountain body to a mountain shadow according to solar altitude angle information, determining a size and a position of a shadow in the altitude image, and processing the rotated altitude image to obtain a shadow position labeled image; (3) performing dilation processing on the obtained shadow position labeled image, and compensating a dilated shadow area; and (4) performing preliminary detection and identification on the infrared remote sensing image in which the shadow area has been compensated, and then performing a secondary judgment by using position correlation, to detect a zonal underground structure.

2 . The method of claim 1 , wherein the determining latitude and longitude information of an area to be detected according to a geographic position of the area to be detected, and then calculating a latitude step size and a longitude step size according to the resolution of an infrared remote sensing image in step (1) specifically comprises sub-steps of:
(1.1.1) obtaining, according to the geographic position of the area to be detected, latitude and longitude information A (x 1 , y 1 ) of a point at the upper left of the area to be detected, and latitude and longitude information B (x 2 , y 2 ) of a point at the lower right of the area to be detected; and (1.1.2) obtaining the resolution, which is k meters, of the infrared remote sensing image, and respectively calculating the longitude step size lon and the latitude step size lat according to the following formulas:
C =sin( y 1 ) 2 *cos( x 1 −x 2 )+cos( y 1 ) 2 ( y 1 =y 2 )
d 1 =R *arccos( C )* Pi/ 180
R=6371.004
lon= k *( x 2 −x 1 )/ d 1
C =cos( y 1 −y 2 ) ( x 1 =x 2 )
d 2 =R *arccos( C )*Pi/180
R=6371.004
lat= k *( y l −y 2 )/ d 2

3 . The method of claim 1 , wherein the acquiring altitude information of the area to be detected according to the latitude and longitude information and the latitude step size and longitude step size of the area to be detected in step (1) is specifically: obtaining latitude and longitude information of each point in the area to be detected according to the latitude and longitude information and the latitude step size and longitude step size of the area to be detected, performing positioning in Google Earth according to the latitude and longitude information of each point, and then acquiring altitude information of each positioned point, to obtain an altitude information image having the same size as a latitude and longitude image, wherein the resolution of the altitude information image is also k meters.

4 . The method of claim 1 , wherein the correcting the obtained altitude information in step (1) specifically comprises:
(1.3.1) processing the altitude information image by using the following formulas to obtain a singular point in altitudes, wherein the singular point and a non-singular point satisfy the following conditions: H (i, j)>H (i+k, j+l)+h (k,l=−1,1), (i, j) in the formula is a singular point, and if H (i, j)<H (i+k, j+l)+h (k, l=−1,1), (i, j) in the formula is a non-singular point, wherein H(i, j) in the formula is an altitude of point (i, j), and H(i+k, j+l) is an altitude of a neighboring point of (i, j); and performing median filtering processing on the singular point to remove the singular point, to obtain a preliminarily corrected altitude image; (1.3.2) performing mean filtering on the preliminarily corrected altitude image by using an m*m-sized template, to correct the altitude image again.

5 . The method of claim 1 , wherein the rotating the corrected altitude image by using solar azimuth angle information in step (2) specifically comprises:
determining a solar azimuth angle θ, and rotating the corrected altitude image by the solar azimuth angle θ, wherein a transformation formula is as follows:
before rotation:

{

x
0

=

r



cos



α

y
0

=

r


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sin
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α

after rotation:

{

x
1

=

r


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cos
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(

α
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θ

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=

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Assignees

• Univ Huazhong Science Tech

Inventors

• Zhang Tianxu
• Hao Longwei
• Ma Wenxuan
• Lu Cen
• Yao Heng
• Wang Yuehuan
• Sang Nong
• Yang Weidong

Classifications

• G06T7/73

  using feature-based methods · CPC title

• G01V9/005 Primary

  by thermal methods, e.g. after generation of heat by chemical reactions · CPC title

• G06V10/60

  relating to illumination properties, e.g. using a reflectance or lighting model · CPC title

• G06V20/13

  Satellite images · CPC title

• G06T2207/10048

  Infrared image · CPC title