使用Python的gdal库读取tif格式遥感图像并将其切割为多个小图

最近实验室有个遥感项目，需要先将tif格式大图切割为小图

# -*- coding: utf-8 -*-
import os
import numpy
from osgeo import gdal

class GRID:
    #读图像文件
    def read_img(self,filename):
        dataset=gdal.Open(filename)       #打开文件

        im_width = dataset.RasterXSize    #栅格矩阵的列数
        im_height = dataset.RasterYSize   #栅格矩阵的行数

        im_geotrans = dataset.GetGeoTransform()  #仿射矩阵
        im_proj = dataset.GetProjection() #地图投影信息
        im_data = dataset.ReadAsArray(0,0,im_width,im_height) #将数据写成数组，对应栅格矩阵

        del dataset 
        return im_proj,im_geotrans,im_data

    #写文件，以写成tif为例
    def write_img(self,filename,im_proj,im_geotrans,im_data):
        #gdal数据类型包括
        #gdal.GDT_Byte, 
        #gdal .GDT_UInt16, gdal.GDT_Int16, gdal.GDT_UInt32, gdal.GDT_Int32,
        #gdal.GDT_Float32, gdal.GDT_Float64

        #判断栅格数据的数据类型
        if 'int8' in im_data.dtype.name:
            datatype = gdal.GDT_Byte
        elif 'int16' in im_data.dtype.name:
            datatype = gdal.GDT_UInt16
        else:
            datatype = gdal.GDT_Float32

        #判读数组维数
        if len(im_data.shape) == 3:
            im_bands, im_height, im_width = im_data.shape
        else:
            im_bands, (im_height, im_width) = 1,im_data.shape 

        #创建文件
        driver = gdal.GetDriverByName("GTiff")            #数据类型必须有，因为要计算需要多大内存空间
        dataset = driver.Create(filename, im_width, im_height, im_bands, datatype)

        dataset.SetGeoTransform(im_geotrans)              #写入仿射变换参数
        dataset.SetProjection(im_proj)                    #写入投影

        if im_bands == 1:
            dataset.GetRasterBand(1).WriteArray(im_data)  #写入数组数据
        else:
            for i in range(im_bands):
                dataset.GetRasterBand(i+1).WriteArray(im_data[i])

        del dataset

if __name__ == "__main__":
    os.chdir(r'E:/data')                        #切换路径到待处理图像所在文件夹
    proj,geotrans,data = GRID().read_img('GF2_PMS1_E116.1_N39.7_20180322_L1A0003077233-MSS1_ORTHO_MS.tif')        #读数据
    print(proj)
    print(geotrans)
    #print(data)
    print(data.shape)
    channel,width,height = data.shape
    for i in range(width//256):#切割成256*256小图
    	for j in range(height//256):
    		cur_image = data[:,i*256:(i+1)*256,j*256:(j+1)*256]
    		GRID().write_img('E:/data/raw1/{}_{}.tif'.format(i,j),proj,geotrans,cur_image) ##写数据

主要参考自：

https://blog.csdn.net/vonuo/article/details/74783291

 

11.17补充：

tif转png/jpg代码：

import os
from osgeo import gdal

open_path = "D:/segmentation/datasets/tif/"
save_path = "D:/segmentation/datasets/png/"

images = os.listdir(open_path)
for image in images:
    im=gdal.Open(os.path.join(open_path,image))
    driver=gdal.GetDriverByName('PNG')
    dst_ds = driver.CreateCopy(os.path.join(save_path,image.split('.')[0]+".png"), im)
    

 

参考：

https://www.jianshu.com/p/5d183afd4458

https://www.osgeo.cn/pygis/gdal-gdalcreate.html

https://gis.stackexchange.com/questions/132298/gdal-c-api-how-to-create-png-or-jpeg-from-scratch/136903