使用osgeo库写一段遥感影像土壤颜色增强的python代码

以下是使用osgeo库进行遥感影像土壤颜色增强的Python代码示例：

# 导入所需库
import os
import numpy as np
from osgeo import gdal, gdal_array, osr

# 打开遥感影像文件
input_file = 'path/to/input/image.tif'
dataset = gdal.Open(input_file, gdal.GA_ReadOnly)

# 读取影像数据和元数据
data = dataset.ReadAsArray().astype(np.float32)
projection = osr.SpatialReference()
projection.ImportFromWkt(dataset.GetProjection())
transform = dataset.GetGeoTransform()

# 确定红、绿、蓝颜色波段索引
red_band = 3
green_band = 2
blue_band = 1

# 针对每个波段进行土壤颜色增强
red = data[red_band-1]
green = data[green_band-1]
blue = data[blue_band-1]

# 计算土壤颜色增强系数
soil_enhancement_coefficient = (2 * red - green - blue) / (red + green + blue)

# 将土壤颜色增强系数应用于红、绿、蓝波段
red_enhanced = red * (1 + soil_enhancement_coefficient)
green_enhanced = green * (1 + soil_enhancement_coefficient)
blue_enhanced = blue * (1 + soil_enhancement_coefficient)

# 将增强后的波段数据写入输出文件
output_file = 'path/to/output/image.tif'
driver = gdal.GetDriverByName('GTiff')
rows, cols = red_enhanced.shape
out_dataset = driver.Create(output_file, cols, rows, 3, gdal.GDT_Float32)
out_dataset.SetGeoTransform(transform)
out_dataset.SetProjection(projection.ExportToWkt())
out_dataset.GetRasterBand(1).WriteArray(red_enhanced)
out_dataset.GetRasterBand(2).WriteArray(green_enhanced)
out_dataset.GetRasterBand(3).WriteArray(blue_enhanced)
out_dataset.FlushCache()

需要注意的是，以上代码仅适用于RGB图像，如果是多光谱遥感影像，需要根据实际情况修改代码。