from osgeo import ogr, gdal import os import argparse import numpy as np from PIL import Image def get_filename_without_ext(path): base_name = os.path.basename(path) if '.' not in base_name or base_name.startswith('.'): return base_name return base_name.rsplit('.', 1)[0] def read_tif(path): dataset = gdal.Open(path) # 打开TIF文件 if dataset is None: print("无法打开文件") return None, None, None cols = dataset.RasterXSize # 图像宽度 rows = dataset.RasterYSize # 图像高度 bands = dataset.RasterCount im_proj = dataset.GetProjection() # 获取投影信息 im_Geotrans = dataset.GetGeoTransform() # 获取仿射变换信息 im_data = dataset.ReadAsArray(0, 0, cols, rows) # 读取栅格数据为NumPy数组 print("行数：", rows) print("列数：", cols) print("波段：", bands) del dataset # 关闭数据集 return im_proj, im_Geotrans, im_data def write_envi(im_data, im_geotrans, im_proj, output_path): """ 将数组数据写入ENVI格式文件 :param im_data: 输入的numpy数组（2D或3D） :param im_geotrans: 仿射变换参数（6元组） :param im_proj: 投影信息（WKT字符串） :param output_path: 输出文件路径（无需扩展名，会自动生成.dat和.hdr） """ im_bands = 1 im_height, im_width = im_data.shape # 创建ENVI格式驱动 driver = gdal.GetDriverByName("ENVI") dataset = driver.Create(output_path, im_width, im_height, 1, gdal.GDT_Byte) if dataset is not None: dataset.SetGeoTransform(im_geotrans) # 设置地理变换参数 dataset.SetProjection(im_proj) # 设置投影 dataset.GetRasterBand(1).WriteArray(im_data) dataset.FlushCache() # 确保数据写入磁盘 dataset = None # 关闭文件 def Strech_linear(im_data): im_data_dB=10*np.log10(im_data) immask=np.isfinite(im_data_dB) infmask = np.isinf(im_data_dB) imvail_data=im_data[immask] im_data_dB=0 minvalue=np.nanmin(imvail_data) maxvalue=np.nanmax(imvail_data) infmask = np.isinf(im_data_dB) im_data[infmask] = minvalue-100 im_data = (im_data - minvalue) / (maxvalue - minvalue) * 254+1 im_data=np.clip(im_data,0,255) return im_data.astype(np.uint8) def Strech_linear1(im_data): im_data_dB = 10 * np.log10(im_data) immask = np.isfinite(im_data_dB) infmask = np.isinf(im_data_dB) imvail_data = im_data[immask] im_data_dB=0 minvalue=np.percentile(imvail_data,1) maxvalue = np.percentile(imvail_data, 99) im_data[infmask] = minvalue - 100 im_data = (im_data - minvalue) / (maxvalue - minvalue) * 254 + 1 im_data = np.clip(im_data, 0, 255) return im_data.astype(np.uint8) def Strech_linear2(im_data): im_data_dB = 10 * np.log10(im_data) immask = np.isfinite(im_data_dB) infmask = np.isinf(im_data_dB) imvail_data = im_data[immask] im_data_dB = 0 minvalue = np.percentile(imvail_data, 2) maxvalue = np.percentile(imvail_data, 98) im_data[infmask] = minvalue - 100 im_data = (im_data - minvalue) / (maxvalue - minvalue) * 254 + 1 im_data = np.clip(im_data, 0, 255) return im_data.astype(np.uint8) def Strech_linear5(im_data): im_data_dB = 10 * np.log10(im_data) immask = np.isfinite(im_data_dB) infmask = np.isinf(im_data_dB) imvail_data = im_data[immask] im_data_dB = 0 minvalue = np.percentile(imvail_data, 5) maxvalue = np.percentile(imvail_data, 95) im_data[infmask] = minvalue - 100 im_data = (im_data - minvalue) / (maxvalue - minvalue) * 254 + 1 im_data = np.clip(im_data, 0, 255) return im_data.astype(np.uint8) def Strech_SquareRoot(im_data): im_data=np.sqrt(im_data) immask = np.isfinite(im_data) imvail_data = im_data[immask] minvalue=np.nanmin(imvail_data) maxvalue=np.nanmax(imvail_data) im_data = (im_data - minvalue) / (maxvalue - minvalue) * 254 + 1 im_data = np.clip(im_data, 0, 255) return im_data.astype(np.uint8) def DataStrech(im_data,strechmethod): # [,"Linear1","Linear2","Linear5","SquareRoot"] if strechmethod == "Linear" : return Strech_linear(im_data) elif strechmethod == "Linear1": return Strech_linear1(im_data) elif strechmethod == "Linear2": return Strech_linear2(im_data) elif strechmethod == "Linear5": return Strech_linear5(im_data) elif strechmethod == "SquareRoot": return Strech_SquareRoot(im_data) else: return im_data.astype(np.uint8) def stretchProcess(infilepath,outfilepath,strechmethod): im_proj, im_Geotrans, im_data=read_tif(infilepath) envifilepath=get_filename_without_ext(outfilepath)+".bin" envifilepath=os.path.join(os.path.dirname(outfilepath),envifilepath) im_data = DataStrech(im_data,strechmethod) im_data = im_data.astype(np.uint8) write_envi(im_data,im_Geotrans,im_proj,envifilepath) Image.fromarray(im_data).save(outfilepath,compress_level=0) print("图像拉伸处理结束") def getParams(): parser = argparse.ArgumentParser() parser.add_argument('-i','--infile',type=str,default=r"F:\天仪SAR卫星数据集\舰船数据\bc2-sp-org-vv-20250205t032055-021998-000036-0055ee-01.tiff", help='输入shapefile文件') parser.add_argument('-o', '--outfile',type=str,default=r"F:\天仪SAR卫星数据集\舰船数据\bc2-sp-org-vv-20250205t032055-021998-000036-0055ee-01.png", help='输出geojson文件') group = parser.add_mutually_exclusive_group() group.add_argument( '--Linear', action='store_const', const='Linear', dest='method', help='线性拉伸' ) group.add_argument( '--Linear1prec', action='store_const', const='Linear1', dest='method', help='1%线性拉伸' ) group.add_argument( '--Linear2prec', action='store_const', const='Linear2', dest='method', help='2%线性拉伸' ) group.add_argument( '--Linear5prec', action='store_const', const='Linear5', dest='method', help='5%线性拉伸' ) group.add_argument( '--SquareRoot', action='store_const', const='SquareRoot', dest='method', help='平方根拉伸' ) parser.set_defaults(method='SquareRoot') args = parser.parse_args() return args if __name__ == '__main__': parser = getParams() intiffPath=parser.infile outbinPath=parser.outfile methodstr=parser.method print('infile=',intiffPath) print('outfile=',outbinPath) print('method=',methodstr) stretchProcess(intiffPath, outbinPath, methodstr)