基于python实现遥感影像预览图生成

目的

遥感影像通常无法直接查看，还需要经过专业软件打开，才能看到其具体内容。最近，需要开发对遥感影像直接生成预览图，就使用GDAL提取波段信息，通过opencv写入图片

环境

• python3.5
• gdal2.4.1
• opencv-python

代码

 

from osgeo import gdal
import cv2
import numpy as np

np.seterr(divide='ignore', invalid='ignore')


def create_preview(dataset, target_path, red=1, green=2, blue=3):
    """
    生成遥感影像的预览图
    :param dataset: 影像数据
    :param red: 预览图红色采用影像的波段索引
    :param green: 预览图绿色采用影像的波段索引
    :param blue: 预览图蓝色采用影像的波段索引
    :param target_path: 预览图存储地址
    :return:
    """
    band_count = dataset.RasterCount
    cols = dataset.RasterXSize  # 列数
    rows = dataset.RasterYSize  # 行数
    # 多波段影像根据红绿蓝索引合成图片
    if band_count >= 3:
        band_red = dataset.GetRasterBand(red)
        data_red = translate(band_red, cols, rows)
        band_green = dataset.GetRasterBand(green)
        data_green = translate(band_green, cols, rows)
        band_blue = dataset.GetRasterBand(blue)
        data_blue = translate(band_blue, cols, rows)

        x = np.zeros([rows, cols, 3], dtype=np.uint8)
        for row_index in range(rows):
            for col_index in range(cols):
                x[row_index][col_index][0] = data_red[row_index][col_index]
                x[row_index][col_index][1] = data_green[row_index][col_index]
                x[row_index][col_index][2] = data_blue[row_index][col_index]
        cv2.imwrite(target_path, x)
    # 单波段影像直接合成灰度
    else:
        band = dataset.GetRasterBand(1)
        cv2.imwrite(target_path, translate(band, cols, rows))


def translate(band, cols, rows):
    """将一个波段的值转到0-255的区间"""
    band_data = band.ReadAsArray(0, 0, cols, rows)
    min = band.GetMinimum()
    max = band.GetMaximum()
    nodata = band.GetNoDataValue()
    band_data[band_data == nodata] = min
    band_data = band_data / max * 255
    return band_data.astype(np.uint8)


driver = gdal.GetDriverByName('GTiff')
# 多波段影像
dataset = gdal.Open("E:/商丘yx/t50smc_20181101t025839_b01.img")
target_path = "C:\\Users\\Administrator\\Pictures\\test_copy1.png"
create_preview(dataset, target_path, red=8, green=5, blue=4)

结果

选择的波段可能不太适合，生成的颜色偏暗

 

结果预览

存在问题

• 多波段影像效率低
• 生成的预览图太大