Python高光谱遥感影像处理问题详细分析讲解

目录

• 前言
• 1.波段合并
• 2.波段拆分
• 3.影像裁剪
• 4.批量影像裁剪

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。

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