均值滤波处理Geotiff影像

### 使用均值滤波处理 Geotiff 影像

对于 Geotiff 影像的均值滤波处理，可以利用 `GDAL` 进行影像读取和写入操作，并借助 `OpenCV` 实现均值滤波功能。下面展示一段 Python 代码来完成这一过程。

#### 安装依赖库
确保安装了必要的 Python 库：

pip install numpy opencv-python gdal

#### 均值滤波处理代码实现

import cv2
from osgeo import gdal, ogr, osr
import numpy as np


def read_geotiff(file_path):
    dataset = gdal.Open(file_path)
    cols = dataset.RasterXSize
    rows = dataset.RasterYSize
    bands_num = dataset.RasterCount
    
    geotransform = dataset.GetGeoTransform()
    projection = dataset.GetProjection()

    band_data = []
    for i in range(bands_num):
        band = dataset.GetRasterBand(i + 1).ReadAsArray(0, 0, cols, rows)
        band_data.append(band)

    return np.array(band_data), geotransform, projection


def write_geotiff(filename, array, geotransform, projection):
    driver = gdal.GetDriverByName('GTiff')
    outdata = driver.Create(filename, array.shape[2], array.shape[1], array.shape[0], gdal.GDT_UInt16)
    
    for i in range(array.shape[0]):
        outband = outdata.GetRasterBand(i + 1)
        outband.WriteArray(array[i])
        
    outdata.SetGeoTransform(geotransform)  
    outdata.SetProjection(projection)   
    outdata.FlushCache()                  # Write to disk.
    

input_file = 'path_to_input.tif'
output_file = 'path_to_output_filtered.tif'

# Read GeoTIFF file and get its metadata
image_array, geo_transform, proj_info = read_geotiff(input_file)[^1]

filtered_bands = []

for single_band in image_array:
    filtered_image = cv2.blur(single_band,(5,5))  # Apply mean filter with kernel size of 5x5
    filtered_bands.append(filtered_image)

write_geotiff(output_file, np.array(filtered_bands), geo_transform, proj_info)

此段程序首先定义两个辅助函数用于读取与保存 Geotiff 文件；接着通过调用 OpenCV 的 blur 函数对每一波段应用均值滤波器，最后将处理后的数据重新组合并存储回新的 Geotiff 文件中。