前言
在写波段配准相关代码时经常需要用到tif影像的波段合成和分解，虽然可以用ENVI才处理，但是每次都要打开再设置一些参数有些麻烦，所以本着“独立自主、自力更生”的原则就写了些脚本来处理这个需求。又写了个批量裁剪影像的脚本。这里简单总结归纳一下。
1.波段合并
# coding=utf-8
import sys
import cv2
import functions as fun
import os
if __name__ == '__main__':
if sys.argv.__len__() >= 2:
if sys.argv[1] == 'help' or sys.argv[1] == 'HELP':
print("Function description:")
print("Join several bands into one file.")
print("\nUsage instruction:")
print("example.exe [img_dir] [img_type] [out_path]")
print("[img_dir]:The input dir that contains band data.")
print("[img_type]:The file type of band data,tif or png etc.")
print("[out_path]:The filename of joined image.")
print("Please note that these band data should have same height and width.")
print("\nUsage example:")
print("Tool_JoinBands.exe C:\\tif tif C:\\tifout\\joined.tif")
os.system('pause')
else:
img_dir = sys.argv[1]
img_type = sys.argv[2]
out_path = sys.argv[3]
paths, names, files = fun.findAllFiles(img_dir, img_type)
bands_data = []
# 对于tif文件，统一用gdal打开并输出为tif文件
if img_type.endswith('tif') or img_type.endswith('TIF') or img_type.endswith('TIFF') or img_type.endswith(
'tiff'):
for i in range(files.__len__()):
band_data = fun.readTifImage(files[i])
bands_data.extend(band_data)
print("joined " + (i + 1).__str__() + " bands.")
print(bands_data.__len__().__str__() + " bands in total.")
fun.writeTif(bands_data, out_path)
# 对于所有其它类型的文件，如jpg、png等，统一用OpenCV处理
else:
for i in range(files.__len__()):
band_data = cv2.imread(files[i], cv2.IMREAD_GRAYSCALE)
bands_data.append(band_data)
print("Open image success.")
data = cv2.merge((bands_data[0], bands_data[1], bands_data[2]))
cv2.imwrite(out_path, data)
print("Save image success.")
else:
print("Unknown mode, input 'yourExeName.exe help' to get help information.")
这里简单介绍下代码。经过波段配准后，不同波段的影像已经实现了对齐，所以通过读取各波段影像然后利用GDAL叠加即可。
2.波段拆分
# coding=utf-8
import sys
import os
import cv2
import functions as fun
if __name__ == '__main__':
if sys.argv.__len__() >= 2:
if sys.argv[1] == 'help' or sys.argv[1] == 'HELP':
print("Function description:")
print("Separate and save different band data in one image file.")
print("\nUsage instruction:")
print("example.exe [img_path] [out_dir]")
print("[img_path]:The filename of input image.")
print("[output_dir]:The output dir for different band images.")
print("\nUsage example:")
print("Tool_SeparateBands.exe C:\\tif\\input.tif C:\\tifout")
os.system('pause')
else:
img_path = sys.argv[1]
output_dir = sys.argv[2]
# 对于tif文件，统一用gdal打开并输出为tif文件
if img_path.endswith('tif') or img_path.endswith('TIF') or img_path.endswith('TIFF') or img_path.endswith(
'tiff'):
bands_data = fun.readTifImage(img_path)
for i in range(bands_data.__len__()):
fun.writeTif([bands_data[i]], output_dir + os.path.sep + "band_" + i.__str__().zfill(2) + ".tif")
print("saved " + (i + 1).__str__() + "/" + bands_data.__len__().__str__())
# 对于所有其它类型的文件，如jpg、png等，统一用OpenCV处理
else:
img = cv2.imread(img_path)
print("Open image success.")
band_b, band_g, band_r = cv2.split(img)
cv2.imwrite(output_dir + os.path.sep + "band_b.png", band_b)
cv2.imwrite(output_dir + os.path.sep + "band_g.png", band_g)
cv2.imwrite(output_dir + os.path.sep + "band_r.png", band_r)
print("Save image success.")
else:
print("Unknown mode, input 'yourExeName.exe help' to get help information.")
波段拆分与波段合并相反，直接读取一个多波段的tif影像，然后依次保存各波段数据为单独文件即可。
3.影像裁剪
在之前，要想实现影像裁剪的功能需要借助ENVI等软件，但是ENVI等打开比较慢，还要各种设置，比较麻烦。所以直接写了个脚本来方便地实现功能
# coding=utf-8
import sys
import cv2
import functions as fun
import os
if __name__ == '__main__':
if sys.argv.__len__() >= 2:
if sys.argv[1] == 'help' or sys.argv[1] == 'HELP':
print("Function description:")
print("Select and cut the ROI(region of interest) in a big image file.")
print("\nUsage instruction:")
print("example.exe [img_path] [out_path] [start_x] [start_y] [x_range] [y_range]")
print("[img_path]:The filename of input image.")
print("[out_path]:The filename of output image.")
print("[start_x]:The x coordinate of ROI's left-top point in big image.")
print("[start_y]:The y coordinate of ROI's left-top point in big image.")
print("[x_range]:The range of ROI in x direction(width).")
print("[y_range]:The range of ROI in y direction(height).")
print("\nUsage example:")
print("Tool_ResizeIMG.exe C:\\tif\\input.tif C:\\tifout\\roi.tif 100 200 3000 4000")
os.system('pause')
else:
img_path = sys.argv[1]
out_path = sys.argv[2]
start_x = int(sys.argv[3])
start_y = int(sys.argv[4])
x_range = int(sys.argv[5])
y_range = int(sys.argv[6])
# 对于tif文件，统一用gdal打开并输出为tif文件
if img_path.endswith('tif') or img_path.endswith('TIF') or img_path.endswith('TIFF') or img_path.endswith(
'tiff'):
bands_data = fun.readTifImageWithWindow(img_path, start_x, start_y, x_range, y_range)
fun.writeTif(bands_data, out_path)
# 对于所有其它类型的文件，如jpg、png等，统一用OpenCV处理
else:
bands_data = cv2.imread(img_path)
print("Open image success.")
bands_data_roi = bands_data[start_y:start_y + y_range, start_x:start_x + x_range, :]
cv2.imwrite(out_path, bands_data_roi)
print("Save image success.")
else:
print("Unknown mode, input 'yourExeName.exe help' to get help information.")
影像裁剪实现也相对简单，就是通过设置读取影像范围即可实现对指定区域的裁剪。
4.批量影像裁剪
# coding=utf-8
import sys
import cv2
import functions as fun
import os
if __name__ == '__main__':
if sys.argv.__len__() >= 2:
if sys.argv[1] == 'help' or sys.argv[1] == 'HELP':
print("Function description:")
print("Select and cut the ROI(region of interest) in big image files(Batch mode).")
print("\nUsage instruction:")
print("example.exe [img_dir] [img_type] [output_dir] [start_x] [start_y] [x_range] [y_range]")
print("[img_dir]:The input dir that contains band data.")
print("[img_type]:The file type of band data,tif or png etc.")
print("[output_dir]:The output dir for ROI images.")
print("[start_x]:The x coordinate of ROI's left-top point in big image.")
print("[start_y]:The y coordinate of ROI's left-top point in big image.")
print("[x_range]:The range of ROI in x direction(width).")
print("[y_range]:The range of ROI in y direction(height).")
print("\nUsage example:")
print("Tool_ResizeIMG_Batch.exe C:\\tif tif C:\\tifout 100 200 3000 4000")
os.system('pause')
else:
img_dir = sys.argv[1]
img_type = sys.argv[2]
out_dir = sys.argv[3]
start_x = int(sys.argv[4])
start_y = int(sys.argv[5])
x_range = int(sys.argv[6])
y_range = int(sys.argv[7])
paths, names, files = fun.findAllFiles(img_dir, img_type)
# 对于tif文件，统一用gdal打开并输出为tif文件
if img_type.endswith('tif') or img_type.endswith('TIF') or img_type.endswith('TIFF') or img_type.endswith(
'tiff'):
for i in range(files.__len__()):
bands_data = fun.readTifImageWithWindow(files[i], start_x, start_y, x_range, y_range)
fun.writeTif(bands_data, out_dir + os.path.sep + names[i][:names[i].rfind('.')] + "_cut.tif")
print("cutting " + (i + 1).__str__() + "/" + files.__len__().__str__())
print('cut finished.')
# 对于所有其它类型的文件，如jpg、png等，统一用OpenCV处理
else:
for i in range(files.__len__()):
bands_data = cv2.imread(files[i])
bands_data_roi = bands_data[start_y:start_y + y_range, start_x:start_x + x_range, :]
cv2.imwrite(out_dir + os.path.sep + "band_" + (i + 1).__str__().zfill(2) + ".jpg", bands_data_roi)
print("cutting " + (i + 1).__str__() + "/" + files.__len__())
print('cut finished.')
else:
print("Unknown mode, input 'yourExeName.exe help' to get help information.")
相比于单张影像裁剪，批量裁剪就是多加了个循环，实现了批量操作，也比较简单。
5.模块functions如下:
functions.py
# coding=utf-8
import os
import cv2
import numpy as np
from osgeo import gdal
from gdalconst import *
def readTifImage(img_path):
data = []
# 以只读方式打开遥感影像
dataset = gdal.Open(img_path, GA_ReadOnly)
if dataset is None:
print("Unable to open image file.")
return data
else:
print("Open image file success.")
bands_num = dataset.RasterCount
print("Image height:" + dataset.RasterYSize.__str__() + " Image width:" + dataset.RasterXSize.__str__())
print(bands_num.__str__() + " bands in total.")
for i in range(bands_num):
# 获取影像的第i+1个波段
band_i = dataset.GetRasterBand(i + 1)
# 读取第i+1个波段数据
band_data = band_i.ReadAsArray(0, 0, band_i.XSize, band_i.YSize)
data.append(band_data)
print("band " + (i + 1).__str__() + " read success.")
return data
def writeTif(bands, path):
if bands is None or bands.__len__() == 0:
return
else:
# 认为各波段大小相等，所以以第一波段信息作为保存
band1 = bands[0]
# 设置影像保存大小、波段数
img_width = band1.shape[1]
img_height = band1.shape[0]
num_bands = bands.__len__()
# 设置保存影像的数据类型
if 'int8' in band1.dtype.name:
datatype = gdal.GDT_Byte
elif 'int16' in band1.dtype.name:
datatype = gdal.GDT_UInt16
else:
datatype = gdal.GDT_Float32
# 创建文件
driver = gdal.GetDriverByName("GTiff")
dataset = driver.Create(path, img_width, img_height, num_bands, datatype)
if dataset is not None:
for i in range(bands.__len__()):
dataset.GetRasterBand(i + 1).WriteArray(bands[i])
print("save image success.")
def readTifImageWithWindow(img_path, start_x, start_y, x_range, y_range):
data = []
# 以只读方式打开遥感影像
dataset = gdal.Open(img_path, GA_ReadOnly)
if dataset is None:
print("Unable to open image file.")
return data
else:
print("Open image file success.")
bands_num = dataset.RasterCount
print("Image height:" + dataset.RasterYSize.__str__() + " Image width:" + dataset.RasterXSize.__str__())
print(bands_num.__str__() + " bands in total.")
for i in range(bands_num):
# 获取影像的第i+1个波段
band_i = dataset.GetRasterBand(i + 1)
# 读取第i+1个波段数据
band_data = band_i.ReadAsArray(start_x, start_y, x_range, y_range)
data.append(band_data)
print("band " + (i + 1).__str__() + " read success.")
return data
def findAllFiles(root_dir, filter):
print("Finding files ends with \'" + filter + "\' ...")
separator = os.path.sep
paths = []
names = []
files = []
# 遍历
for parent, dirname, filenames in os.walk(root_dir):
for filename in filenames:
if filename.endswith(filter):
paths.append(parent + separator)
names.append(filename)
for i in range(paths.__len__()):
files.append(paths[i] + names[i])
print (names.__len__().__str__() + " files have been found.")
paths.sort()
names.sort()
files.sort()
return paths, names,
