如何使用python中的地面控制点对未参考的航空影像进行地理参考

时间:2019-04-15 02:47:00

标签: python image gis gdal rasterio

我有一系列未参考的航空图像,我想使用python进行地理参考。这些图像在空间上是相同的(它们实际上是从视频中提取的帧),我通过在ArcMap中手动对一帧进行地理配准来获取它们的地面控制点。我想将我获得的地面控制点应用于所有后续图像,并因此为每个经过处理的图像获得带有相应世界文件(.jgw)的geo-tiff或jpeg文件。我知道使用arcpy可以做到这一点,但是我没有访问arcpy的权限,并且我真的很想使用免费的开源模块。

我的坐标系是NZGD2000(epsg 2193),这是我要应用于图像的控制点表:

176.412984,-310.977264、1681255.524654、6120217.357425

160.386905,-141.487145、1681158.424227、6120406.821253

433.204947,-310.547238、1681556.948690、6120335.658359

以下是示例图片:https://imgur.com/a/9ThHtOz

我已经阅读了很多有关GDAL和rasterio的信息,但是我对它们没有任何经验,并且无法将我发现的部分代码用于我的特定情况。

光栅尝试:

import cv2
from rasterio.warp import reproject
from rasterio.control import GroundControlPoint
from fiona.crs import from_epsg

img = cv2.imread("Example_image.jpg")

# Creating ground control points (not sure if I got the order of variables right):
points = [(GroundControlPoint(176.412984, -310.977264, 1681255.524654, 6120217.357425)),
          (GroundControlPoint(160.386905, -141.487145, 1681158.424227, 6120406.821253)),
          (GroundControlPoint(433.204947, -310.547238, 1681556.948690, 6120335.658359))]

# The function requires a parameter "destination", but I'm not sure what to put there.
#   I'm guessing this may not be the right function to use
reproject(img, destination, src_transform=None, gcps=points, src_crs=from_epsg(2193),
                        src_nodata=None, dst_transform=None, dst_crs=from_epsg(2193), dst_nodata=None,
                        src_alpha=0, dst_alpha=0, init_dest_nodata=True, warp_mem_limit=0)

GDAL尝试:

from osgeo import gdal 
import osr

inputImage = "Example_image.jpg"
outputImage = "image_gdal.jpg"

dataset = gdal.Open(inputImage) 
I = dataset.ReadAsArray(0,0,dataset.RasterXSize,dataset.RasterYSize)

outdataset = gdal.GetDriverByName('GTiff') 
output_SRS = osr.SpatialReference() 
output_SRS.ImportFromEPSG(2193) 
outdataset = outdataset.Create(outputImage,dataset.RasterXSize,dataset.RasterYSize,I.shape[0]) 
for nb_band in range(I.shape[0]):
    outdataset.GetRasterBand(nb_band+1).WriteArray(I[nb_band,:,:])

# Creating ground control points (not sure if I got the order of variables right):
gcp_list = [] 
gcp_list.append(gdal.GCP(176.412984, -310.977264, 1681255.524654, 6120217.357425))
gcp_list.append(gdal.GCP(160.386905, -141.487145, 1681158.424227, 6120406.821253))
gcp_list.append(gdal.GCP(433.204947, -310.547238, 1681556.948690, 6120335.658359))

outdataset.SetProjection(srs.ExportToWkt()) 
wkt = outdataset.GetProjection() 
outdataset.SetGCPs(gcp_list,wkt)

outdataset = None

我不太了解如何使以上代码正常工作,对此我将不胜感激。

2 个答案:

答案 0 :(得分:2)

我最终读了一本书“用Python进行地理处理”,最后找到了一个对我有用的解决方案。这是我适应问题的代码:

import shutil
from osgeo import gdal, osr

orig_fn = 'image.tif'
output_fn = 'output.tif'

# Create a copy of the original file and save it as the output filename:
shutil.copy(orig_fn, output_fn)
# Open the output file for writing for writing:
ds = gdal.Open(output_fn, gdal.GA_Update)
# Set spatial reference:
sr = osr.SpatialReference()
sr.ImportFromEPSG(2193) #2193 refers to the NZTM2000, but can use any desired projection

# Enter the GCPs
#   Format: [map x-coordinate(longitude)], [map y-coordinate (latitude)], [elevation],
#   [image column index(x)], [image row index (y)]
gcps = [gdal.GCP(1681255.524654, 6120217.357425, 0, 176.412984, 310.977264),
gdal.GCP(1681158.424227, 6120406.821253, 0, 160.386905, 141.487145),
gdal.GCP(1681556.948690, 6120335.658359, 0, 433.204947, 310.547238)]

# Apply the GCPs to the open output file:
ds.SetGCPs(gcps, sr.ExportToWkt())

# Close the output file in order to be able to work with it in other programs:
ds = None

答案 1 :(得分:1)

对于您的gdal方法,只需使用gdal.warp和outdataset应该可以工作,例如

outdataset.SetProjection(srs.ExportToWkt()) 
wkt = outdataset.GetProjection() 
outdataset.SetGCPs(gcp_list,wkt)
gdal.Warp("output_name.tif", outdataset, dstSRS='EPSG:2193', format='gtiff')

这将创建一个新文件output_name.tif。