459 lines
18 KiB
Python
459 lines
18 KiB
Python
"""
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@Project ：microproduct
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@File ：AHVToPolsarpro.PY
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@Function ：将四个极化数据转成bin格式的s2矩阵文件、hdr头文件、config配置文件
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@Author ：LMM
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@Date ：2021/10/19 14:39
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@Version ：1.0.0
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"""
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import os
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import numpy as np
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import glob
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import struct
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from tool.algorithm.image.ImageHandle import ImageHandler
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class AHVToPolSarProS2:
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"""
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全极化影像转换为bin格式S2矩阵，支持polsarpro处理
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"""
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def __init__(self):
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pass
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@staticmethod
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def __ahv_to_s2(ahv_dir):
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"""
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全极化影像转S2矩阵
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:param ahv_dir: 全极化影像文件夹路径
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:return: 极化散射矩阵S2
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"""
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in_tif_paths = list(glob.glob(os.path.join(ahv_dir, '*.tif')))
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if in_tif_paths == []:
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in_tif_paths = list(glob.glob(os.path.join(ahv_dir, '*.tiff')))
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s11, s12, s21, s22 = None, None, None, None
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flag_list = [0, 0, 0, 0]
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for in_tif_path in in_tif_paths:
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# 读取原始SAR影像
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wid=ImageHandler.get_img_width(in_tif_path)
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hei=ImageHandler.get_img_height(in_tif_path)
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# data=np.zeros((2,hei,wid),dtype=float)
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proj, geotrans, data = ImageHandler.read_img(in_tif_path)
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# 获取极化类型
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if 'HH' in os.path.basename(in_tif_path):
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data_real = data[0, :, :] # 获取第一个波段 (实部)
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data_imag = data[1, :, :] # 获取第二个波段 (虚部)
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s11 = data_real + 1j * data_imag
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flag_list[0] = 1
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elif 'HV' in os.path.basename(in_tif_path):
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data_real = data[0, :, :]
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data_imag = data[1, :, :]
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s12 = data_real + 1j * data_imag
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flag_list[1] = 1
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elif 'VH' in os.path.basename(in_tif_path):
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data_real = data[0, :, :]
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data_imag = data[1, :, :]
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s21 = data_real + 1j * data_imag
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flag_list[2] = 1
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elif 'VV' in os.path.basename(in_tif_path):
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data_real = data[0, :, :]
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data_imag = data[1, :, :]
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s22 = data_real + 1j * data_imag
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flag_list[3] = 1
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else:
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continue
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if not flag_list == [1, 1, 1, 1]:
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raise Exception('HH or HV or VH or VV is not in path :%s',ahv_dir)
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return s11, s12, s21, s22
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@staticmethod
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def __ahv_to_s2flatEffect(ahv_dir, flatEffect):
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"""
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全极化影像转S2矩阵
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:param ahv_dir: 全极化影像文件夹路径
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:return: 极化散射矩阵S2
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"""
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in_tif_paths = list(glob.glob(os.path.join(ahv_dir, '*.tif')))
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if in_tif_paths == []:
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in_tif_paths = list(glob.glob(os.path.join(ahv_dir, '*.tiff')))
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s11, s12, s21, s22 = None, None, None, None
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flag_list = [0, 0, 0, 0]
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for in_tif_path in in_tif_paths:
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# 读取原始SAR影像
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wid = ImageHandler.get_img_width(in_tif_path)
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hei = ImageHandler.get_img_height(in_tif_path)
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# data = np.zeros((2, hei, wid), dtype=float)
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proj, geotrans, data = ImageHandler.read_img(in_tif_path)
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# 获取极化类型
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if 'HH' in os.path.basename(in_tif_path):
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data_real = data[0, :, :] # 获取第一个波段 (实部)
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data_imag = data[1, :, :] # 获取第二个波段 (虚部)
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s11 = (data_real + 1j * data_imag) * flatEffect
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flag_list[0] = 1
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elif 'HV' in os.path.basename(in_tif_path):
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data_real = data[0, :, :]
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data_imag = data[1, :, :]
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s12 = (data_real + 1j * data_imag) * flatEffect
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flag_list[1] = 1
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elif 'VH' in os.path.basename(in_tif_path):
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data_real = data[0, :, :]
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data_imag = data[1, :, :]
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s21 = (data_real + 1j * data_imag) * flatEffect
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flag_list[2] = 1
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elif 'VV' in os.path.basename(in_tif_path):
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data_real = data[0, :, :]
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data_imag = data[1, :, :]
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s22 = (data_real + 1j * data_imag) * flatEffect
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flag_list[3] = 1
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else:
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continue
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if not flag_list == [1, 1, 1, 1]:
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raise Exception('HH or HV or VH or VV is not in path :%s', ahv_dir)
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return s11, s12, s21, s22
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def __s2_to_bin(self, out_dir, s11, s12, s21, s22):
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"""
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s2矩阵转bin格式，支持 polsarpro处理
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:param out_dir: 输出的文件夹路径
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:param s11:
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:param s12:
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:param s21
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:param s22:
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:return: bin格式矩阵s2和头文件
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"""
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if not os.path.exists(out_dir):
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os.makedirs(out_dir)
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rows = s11.shape[0]
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cols = s11.shape[1]
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bins_dict = {'s11.bin': s11,
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's12.bin': s12,
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's21.bin': s21,
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's22.bin': s22}
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for name, data in bins_dict.items():
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bin_path = os.path.join(out_dir, name)
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self.__write_slc_img_bin(data, bin_path, name)
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out_hdr_path = bin_path+'.hdr'
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self.__write_bin_hdr(out_hdr_path, bin_path, rows, cols)
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self.__write_config_file(out_dir, rows, cols)
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@staticmethod
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def __write_slc_img_bin(im, file_path, name):
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"""
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写入影像到bin文件中，保存为float32类型
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:param im : 影像矩阵数据，暂支持单通道影像数据
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:param file_path: bin文件的完整路径
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"""
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with open(file_path, 'wb') as f:
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rows = im.shape[0]
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cols = im.shape[1]
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cre_im = np.zeros((rows, 2*cols), dtype=float)
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cre_im[:, ::2] = im.real[0:rows, :] # 存 real
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cre_im[:, 1::2] = im.imag[0:rows, :] # 存 imag
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for row in range(rows):
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cre_im_bin = struct.pack("f" * 2*cols, *np.reshape(cre_im[row, :], (2*cols, 1), order='F'))
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f.write(cre_im_bin)
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f.close()
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# img_array=AHVToPolSarProS2().read_complex_bin_to_array(file_path)
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# real_diff=img_array[0]-im.real
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# imag_diff=img_array[1]-im.imag
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# pass
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@staticmethod
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def write_slc_img_bin(im, file_path):
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"""
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写入影像到bin文件中，保存为float32类型
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:param im : 影像矩阵数据，暂支持单通道影像数据
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:param file_path: bin文件的完整路径
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"""
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with open(file_path, 'wb') as f:
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rows = im.shape[0]
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cols = im.shape[1]
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cre_im = np.zeros((rows, 2 * cols), dtype=float)
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cre_im[:, ::2] = im.real[0:rows, :] # 存 real
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cre_im[:, 1::2] = im.imag[0:rows, :] # 存 imag
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for row in range(rows):
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cre_im_bin = struct.pack("f" * 2 * cols, *np.reshape(cre_im[row, :], (2 * cols, 1), order='F'))
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f.write(cre_im_bin)
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f.close()
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@staticmethod
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def read_complex_bin_to_array(bin_path):
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"""
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读取bin格式二进制数据，输出为矩阵
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:param bin_path : bin文件的路径，包含.bin,.config
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:return : 矩阵信息
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"""
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(bin_dir, bin_name) = os.path.split(bin_path)
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config_path = os.path.join(bin_dir, 'config.txt')
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config = open(config_path, 'r').read().split('\n', -1)
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rows = int(config[1])
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cols = int(config[4])
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bin_file = open(bin_path, 'rb') # 打开二进制文件
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size = os.path.getsize(bin_path) # 获得文件大小
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if (size < rows * cols * 4 * 2) and (size > rows * cols * 4):
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raise Exception(
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'bin size less than rows*cols*4! size:',
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size,
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'byte, rows:',
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rows,
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'cols:',
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cols)
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bin_data = np.zeros([rows, cols*2], dtype=np.float32)
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img_array = np.zeros([2, rows, cols], dtype=np.float32)
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for row in range(rows):
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data = bin_file.read(4 * cols * 2) # 每次读取一行的二进制数据
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row_data = struct.unpack('f' * cols*2, data) # 转为一行float数据
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bin_data[row, :] = row_data
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bin_file.close()
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img_array[0] = bin_data[:, ::2] # real
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img_array[1] = bin_data[:, 1::2] # imag
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return img_array
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@staticmethod
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def read_none_complex_bin_to_array(bin_path):
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"""
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读取bin格式二进制数据，输出为矩阵
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:param bin_path : bin文件的路径，包含.bin,.config
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:return : 矩阵信息
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"""
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(bin_dir, bin_name) = os.path.split(bin_path)
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config_path = os.path.join(bin_dir, 'config.txt')
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config = open(config_path, 'r').read().split('\n', -1)
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rows = int(config[1])
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cols = int(config[4])
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bin_file = open(bin_path, 'rb') # 打开二进制文件
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size = os.path.getsize(bin_path) # 获得文件大小
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if size < rows * cols * 4:
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raise Exception(
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'bin size less than rows*cols*4! size:',
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size,
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'byte, rows:',
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rows,
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'cols:',
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cols)
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img = np.zeros([rows, cols], dtype=np.float32)
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for row in range(rows):
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data = bin_file.read(4 * cols) # 每次读取一行的二进制数据
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row_data = struct.unpack('f' * cols, data) # 转为一行float数据
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img[row, :] = row_data
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bin_file.close()
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return img
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@staticmethod
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def __write_bin_hdr(out_hdr_path, bin_path, rows, cols):
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"""
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写入影像的头文件
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:param out_hdr_path : 头文件的路径
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:param bin_path: bin文件的路径
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:param rows: 影像的行数
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:param cols: 影像的列数
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"""
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h1 = 'ENVI'
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h2 = 'description = {'
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h3 = 'ENVI File, Created [] }'
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h4 = 'samples = ' + str(cols) # 列
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h5 = 'lines = ' + str(rows) # 行
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h6 = 'bands = 1 ' # 波段数
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h7 = 'header offset = 0'
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h8 = 'file type = ENVI Standard'
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h9 = 'data type = 6' # 数据格式 6代表复数
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h10 = 'interleave = bsq' # 存储格式
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h11 = 'sensor type = Unknown'
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h12 = 'byte order = 0'
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h13 = 'wavelength units = Unknown'
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h14 = 'complex function = Power'
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h = [h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11, h12, h13, h14]
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doc = open(out_hdr_path, 'w')
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for i in range(0, 14):
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print(h[i], end='', file=doc)
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print('\n', end='', file=doc)
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doc.close()
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@staticmethod
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def write_bin_hdr(out_hdr_path, rows, cols):
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"""
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写入影像的头文件
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:param out_hdr_path : 头文件的路径
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:param bin_path: bin文件的路径
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:param rows: 影像的行数
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:param cols: 影像的列数
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"""
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h1 = 'ENVI'
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h2 = 'description = {'
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h3 = 'ENVI File, Created [] }'
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h4 = 'samples = ' + str(cols) # 列
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h5 = 'lines = ' + str(rows) # 行
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h6 = 'bands = 1 ' # 波段数
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h7 = 'header offset = 0'
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h8 = 'file type = ENVI Standard'
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h9 = 'data type = 6' # 数据格式 6代表复数
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h10 = 'interleave = bsq' # 存储格式
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h11 = 'sensor type = Unknown'
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h12 = 'byte order = 0'
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h13 = 'wavelength units = Unknown'
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h14 = 'complex function = Power'
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h = [h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11, h12, h13, h14]
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doc = open(out_hdr_path, 'w')
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for i in range(0, 14):
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print(h[i], end='', file=doc)
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print('\n', end='', file=doc)
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doc.close()
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@staticmethod
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def __write_phi_bin_hdr(out_hdr_path, rows, cols):
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"""
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写入影像的头文件
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:param out_hdr_path : 头文件的路径
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:param rows: 影像的行数
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:param cols: 影像的列数
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"""
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h1 = 'ENVI'
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h2 = 'description = {'
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h3 = 'ENVI File, Created [] }'
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h4 = 'samples = ' + str(cols) # 列
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h5 = 'lines = ' + str(rows) # 行
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h6 = 'bands = 1 ' # 波段数
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h7 = 'header offset = 0'
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h8 = 'file type = ENVI Standard'
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h9 = 'data type = 4' # 数据格式
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h10 = 'interleave = bsq' # 存储格式
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h11 = 'sensor type = Unknown'
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h12 = 'byte order = 0'
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h13 = 'wavelength units = Unknown'
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h14 = 'complex function = Power'
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h = [h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11, h12, h13, h14]
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doc = open(out_hdr_path, 'w')
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for i in range(0, 14):
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print(h[i], end='', file=doc)
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print('\n', end='', file=doc)
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doc.close()
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@staticmethod
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def __write_config_file(out_config_dir, rows, cols):
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"""
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写入polsarpro配置文件
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:param out_config_dir : 配置文件路径
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:param rows: 影像的行数
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:param cols: 影像的列数
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"""
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h1 = 'Nrow'
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h2 = str(rows)
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h3 = '---------'
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h4 = 'Ncol'
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h5 = str(cols)
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h6 = '---------'
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h7 = 'PolarCase'
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h8 = 'monostatic'
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# h8 = 'bistatic'
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h9 = '---------'
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h10 = 'PolarType'
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h11 = 'full'
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h = [h1, h2, h3, h4, h5, h6, h7, h8, h9, h10, h11]
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out_config_path = os.path.join(out_config_dir, 'config.txt')
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doc = open(out_config_path, 'w')
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for i in range(0, 11):
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print(h[i], end='', file=doc)
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print('\n', end='', file=doc)
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doc.close()
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def api_ahv_to_polsarpro_s2(self, out_file_dir, in_ahv_dir):
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s11, s12, s21, s22 = self.__ahv_to_s2(in_ahv_dir)
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self.__s2_to_bin(out_file_dir, s11, s12, s21, s22)
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def api_ahv_to_polsarpro_s2flatEffect(self, out_file_dir, in_ahv_dir, flatEffect):
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print("in_ahv_dir:\t",in_ahv_dir)
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s11, s12, s21, s22 = self.__ahv_to_s2flatEffect(in_ahv_dir, flatEffect)
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self.__s2_to_bin(out_file_dir, s11, s12, s21, s22)
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@staticmethod
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def array_bin(file_path, array):
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"""
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矩阵转bin文件
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:return:
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"""
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with open(file_path, 'wb') as f:
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rows, cols = array.shape[0], array.shape[1]
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for row in range(rows):
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cre_im_bin = struct.pack("f" * cols, *np.reshape(array[row, :], (cols, 1), order='F'))
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f.write(cre_im_bin)
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f.close()
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out_hdr_path = file_path + '.hdr'
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AHVToPolSarProS2().__write_phi_bin_hdr(out_hdr_path, rows, cols)
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if __name__ == '__main__':
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atp = AHVToPolSarProS2()
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ahv_path = r'D:\micro\LWork\VegetationHeight\Temporary\preprocessed\AuxiliarySar'
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out_dir = r'D:\micro\LWork\VegetationHeight\Temporary\preprocessed\flat_s'
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flat = r'D:\micro\LWork\VegetationHeight\Temporary\preprocessed\FlatEffect\flatEffect_path.tif'
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data = ImageHandler.get_data(flat)
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data = np.exp(1j * data)
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atp.api_ahv_to_polsarpro_s2flatEffect(out_dir, ahv_path, data)
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# pro=ImageHandler().get_projection('G:\comparebin\AuxiliarySar\GF3_MYN_QPSI_011437_E98.7_N31.3_20181012_L1A_HH_L10003514924_caijian.tif')
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# geo=ImageHandler().get_geotransform('G:\comparebin\AuxiliarySar\GF3_MYN_QPSI_011437_E98.7_N31.3_20181012_L1A_HH_L10003514924_caijian.tif')
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#
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# # ahv_path = 'D:\\DATA\\GAOFEN3\\2598957_Paris\\'
|
||
# out_file_path = r'G:\comparebin\AuxiliarySar_slc'
|
||
# atp.api_ahv_to_polsarpro_s2(out_file_path, ahv_path)
|
||
#
|
||
#
|
||
# arrayt_hh = atp.read_complex_bin_to_array(r'G:\comparebin\AuxiliarySar_slc\s11.bin')
|
||
# filename_hh='G:\comparebin\AuxiliarySar_tiff\GF3_MYN_QPSI_011437_E98.7_N31.3_20181012_L1A_HH_L10003514924_caijian-fuben.tif'
|
||
# ImageHandler().write_img(filename_hh, pro, geo, arrayt_hh, no_data='null')
|
||
# arrayt_hh2=ImageHandler().get_data(filename_hh)
|
||
# filename_hh3="G:\comparebin\AuxiliarySar\GF3_MYN_QPSI_011437_E98.7_N31.3_20181012_L1A_HH_L10003514924_caijian.tif"
|
||
# arrayt_hh3=ImageHandler().get_data(filename_hh3)
|
||
#
|
||
# diff_1_hh=arrayt_hh2-arrayt_hh
|
||
# diff_2_hh=arrayt_hh2-arrayt_hh3
|
||
#
|
||
# arrayt_hv = atp.read_complex_bin_to_array(r'G:\comparebin\AuxiliarySar_slc\s12.bin')
|
||
# filename_hv='G:\comparebin\AuxiliarySar_tiff\GF3_MYN_QPSI_011437_E98.7_N31.3_20181012_L1A_HV_L10003514924-fuben.tif'
|
||
# ImageHandler().write_img(filename_hv, pro, geo, arrayt_hv, no_data='null')
|
||
# arrayt_hv2=ImageHandler().get_data(filename_hv)
|
||
# filename_hv3="G:\comparebin\AuxiliarySar\GF3_MYN_QPSI_011437_E98.7_N31.3_20181012_L1A_HV_L10003514924.tif"
|
||
# arrayt_hv3=ImageHandler().get_data(filename_hv3)
|
||
#
|
||
# diff_1_hv = arrayt_hv2 - arrayt_hv
|
||
# diff_2_hv=arrayt_hv2-arrayt_hv3
|
||
#
|
||
# arrayt_vh = atp.read_complex_bin_to_array(r'G:\comparebin\AuxiliarySar_slc\s21.bin')
|
||
# filename_vh='G:\comparebin\AuxiliarySar_tiff\GF3_MYN_QPSI_011437_E98.7_N31.3_20181012_L1A_VH_L10003514924-fuben.tif'
|
||
# ImageHandler().write_img(filename_vh, pro, geo, arrayt_vh, no_data='null')
|
||
# arrayt_vh2 = ImageHandler().get_data(filename_vh)
|
||
# filename_vh3="G:\comparebin\AuxiliarySar\GF3_MYN_QPSI_011437_E98.7_N31.3_20181012_L1A_VH_L10003514924.tif"
|
||
# arrayt_vh3=ImageHandler().get_data(filename_vh3)
|
||
#
|
||
# diff_1_vh = arrayt_vh2 - arrayt_vh
|
||
# diff_2_vh = arrayt_vh2 - arrayt_vh3
|
||
#
|
||
# arrayt_VV = atp.read_complex_bin_to_array(r'G:\comparebin\AuxiliarySar_slc\s22.bin')
|
||
# filename_VV='G:\comparebin\AuxiliarySar_tiff\GF3_MYN_QPSI_011437_E98.7_N31.3_20181012_L1A_VV_L10003514924-fuben.tif'
|
||
# ImageHandler().write_img(filename_VV, pro, geo, arrayt_VV, no_data='null')
|
||
# arrayt_VV2 = ImageHandler().get_data(filename_VV)
|
||
# filename_VV3="G:\comparebin\AuxiliarySar\GF3_MYN_QPSI_011437_E98.7_N31.3_20181012_L1A_VV_L10003514924.tif"
|
||
# arrayt_VV3=ImageHandler().get_data(filename_VV3)
|
||
#
|
||
# diff_VV = arrayt_VV2 - arrayt_VV
|
||
# diff_VV2 = arrayt_VV2 - arrayt_VV3
|
||
# print("done")
|