给的PAN数据没有Resize,于是选择结合这段代码

#!/usr/bin/env python
# coding=utf-8
'''
@Author: wjm
@Date: 2020-06-13 20:12:23
LastEditTime: 2024-04-08 10:34:01
@Description: file content
'''
import numpy as np 
import glob, os, h5py
import os
import cv2
from scipy import misc
from PIL import Image
Image.MAX_IMAGE_PIXELS = None

class image_to_patch:

    def __init__(self, patch_size, scale, ms_path, ms_image_path, pan_path, pan_image_path):

        self.stride = patch_size
        self.scale = scale
        self.ms_path = ms_path
        self.ms_image_path = ms_image_path
        self.pan_path = pan_path
        self.pan_image_path = pan_image_path

        if not os.path.exists(ms_image_path):
            os.mkdir(ms_image_path)
        if not os.path.exists(pan_image_path):
            os.mkdir(pan_image_path)

    def to_patch(self):

        #read MS image, CMYK space
        img_ms = self.imread(self.ms_path)
        img_ms = self.modcrop(img_ms, self.scale)

        #read PAN image, Gray space
        img_pan = self.imread(self.pan_path)
        img_pan = self.modcrop(img_pan, self.scale)

        # high, width
        h, w  = img_ms.size
        n_ms = 1
        n_pan = 1

        # MS image
        for x in range(0, h - self.stride, self.stride):
            for y in range(0, w - self.stride, self.stride):
                box = [x, y, x + self.stride, y + self.stride]
                sub_img_label = img_ms.crop(box)
                sub_img_label.save(os.path.join(self.ms_image_path, str(n_ms)+'.tif'))
                n_ms = n_ms + 1

        # PAN image
        for x in range(0, h - self.stride, self.stride):
            for y in range(0, w - self.stride, self.stride):
                box = [x, y, x + self.stride, y + self.stride]
                sub_img_label = img_pan.crop(box)
                sub_img_label.save(os.path.join(self.pan_image_path, str(n_pan)+'.tif'))
                n_pan = n_pan + 1

    def imread(self, path):
        img = Image.open(path)
        return img

    def modcrop(self, img, scale =3):
        h, w = img.size
        h = (h // scale) * scale
        w = (w // scale) * scale
        box=(0,0,h,w)
        img = img.crop(box)
        return img  

class downsample:

    def __init__(self, pan_pach, scale, d_pan_path):
        image = Image.open(pan_pach).convert('L')
        d_image = image.resize((int(image.size[0]/scale),int(image.size[1]/scale)), Image.BICUBIC) 
        d_image.save(d_pan_path)


if __name__ == '__main__':
    image_size = 1024
    scale = 4
    ms_pach = r'../MS.tif'
    ms_image_path = r'./ms'
    pan_pach = r'H:\数据集\4 WorldView-4\pan_8'  ### PAN图像存在的地方
    pan_image_path = r'./pan' ###

    # downsample pan image
    for i in range(0,500):
        pan_pachs =  os.path.join(pan_pach, str(i)+'.tif')
        downsample(pan_pachs, scale, os.path.join(r'H:\数据集\4 WorldView-4\pan', str(i)+'.tif'))

    # image to patch
    # task = image_to_patch(image_size, scale, ms_pach, ms_image_path, pan_pach, pan_image_path)
    # task.to_patch()

制作MTF图像,要注意sensor，和每次数据集里面的图片数量

%% MTF filters the image I_MS using a Gaussin filter matched with the Modulation Transfer Function (MTF) of the MultiSpectral (MS) sensor. 
clear; close all;
addpath Tools;

path = 'H:\数据集\1 IKONOS\';
sensor = 'IKONOS'; %% QB, IKONOS, GeoEye1, WV4, WV2, WV3
scale = 4;

for i = 0 : 199
    path_ms = strcat(path, 'ms\', num2str(i), '.tif');
    ms = imread(path_ms);
    image_ms = double(ms);
    image_ms = MTF(image_ms, sensor ,scale);
    if exist(strcat(path,'/mtf/')) == 0
        mkdir(strcat(path,'/mtf/'));
    end
    str1 = strcat(path, '/mtf/', num2str(i), '.tif');
    imwrite(uint8(image_ms), str1, 'tif');
end