Brovey图像融合方法+Python代码
1、方法原理
原理：Brovey变换融合又叫做比值变换融合，通过对多光谱数据进行归一化后，与高分辨率影像进行乘积来增加影像信息；
2、实现代码
# coding=utf-8
'''
Created on 2020-6-1
@author: jiangao
Project: Brovey图像融合方法
'''
import numpy as np
import cv2
import scipy.misc as smi
from osgeo import gdal
from PIL import Image
def gdal_open(path):
"""
读取图像函数
输入：图像路径
返回：np.ndArray格式的三维数组
"""
data = gdal.Open(path)
col = data.RasterXSize#读取图像长度
row = data.RasterYSize#读取图像宽度
data_array_r = data.GetRasterBand(1).ReadAsArray(0,0,col,row).astype(np.float)#读取图像第一波段并转换为数组
data_array_g = data.GetRasterBand(2).ReadAsArray(0,0,col,row).astype(np.float)#读取图像第二波段并转换为数组
data_array_b = data.GetRasterBand(3).ReadAsArray(0,0,col,row).astype(np.float)#读取图像第三波段并转换为数组
data_array = np.array((data_array_r,data_array_g,data_array_b))
return data_array
def imresize(data_low,data_high):
"""
图像缩放函数
输入：np.ndArray格式的三维数组
返回：np.ndArray格式的三维数组
"""
band , col , row = data_high.shape
data = np.zeros(((band,col,row)))
for i in range(0,band):
data[i] = smi.imresize(data_low[i],(col,row))
return data
def brovey(data_low,data_high):
"""
色彩标准化融合函数
输入：np.ndArray格式的三维数组
返回：可绘出图像的utf-8格式的三维数组
"""
band , col , row = data_low.shape
total = 0
for i in range(0,band):
total = total + data_low[i]
RGB = np.zeros(((band,col,row)))
for i in range(0,band):
RGB[i] = data_low[i] * data_high[i] / total
min_val = np.min(RGB.ravel())
max_val = np.max(RGB.ravel())
RGB = np.uint8((RGB.astype(np.float) - min_val) / (max_val - min_val) * 255)
RGB = Image.fromarray(cv2.merge([RGB[0],RGB[1],RGB[2]]))
return RGB
def main(path_low,path_high):
data_low = gdal_open(path_low)
data_high = gdal_open(path_high)
data_low = imresize(data_low,data_high)
RGB = brovey(data_low,data_high)
RGB.save('Brovey.png','png')
if __name__ == "__main__":
path_low = 'RGB.tif'
path_high = 'Band8.tif'
main(path_low,path_high)
3、执行结果
RGB图像：
高分全色波段影像：
Brovey融合影像：
