tangchao0503/corning410_radiance_calibration
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1. 使用scipy.interpolate.interp1d重采样能量曲线到影像的波段；

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2. 修改：使用spectral.envi.read_envi_header读取envi头文件；
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tangchao0503
2023-06-24 21:33:36 +08:00
parent 8f143e51cc
commit 96c0da3c36
1 changed files with 28 additions and 5 deletions
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31
1.1radiance_calibration_300tc.py
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@ -10,6 +10,8 @@ from radiance_calibration_ui import Ui_MainWindow
from library.multithread import Worker
import sys, traceback
from osgeo import gdal
from scipy.interpolate import interp1d
import spectral
from PyQt5.QtWidgets import QMainWindow, QFileDialog, QApplication
from PyQt5.QtCore import Qt
@ -142,8 +144,16 @@ class RadianceCalibration():
return os.path.splitext(file_path)[0] + ".bip.hdr"
def write_fields_to_hdrfile(self, fields, hdr_file):
header_tmp = spectral.envi.read_envi_header(hdr_file)
with open(hdr_file, "a", encoding='utf-8') as f:
for key in fields.keys():
if key in header_tmp or key == "description":
continue
if type(fields[key]) == list:
f.write(key + " = {" + ", ".join(fields[key]) + "}\n")
else:
f.write(key + " = " + fields[key] + "\n")
def process_hdr(self, hdr_file_path, envi_header_dict):
@ -193,9 +203,23 @@ class RadianceCalibration():
# 读取影像
img_proj, img_geotrans, self.img_data = self.read_img(self.dn_file_path)
dn_hdr = self.get_envi_header_dict(self.get_hdr_filename(self.dn_file_path))
# dn_hdr = self.get_envi_header_dict(self.get_hdr_filename(self.dn_file_path))
dn_hdr = spectral.envi.read_envi_header(self.get_hdr_filename(self.dn_file_path))
img_dark_proj, img_dark_geotrans, self.img_dark_data = self.read_img(self.dark_file_path)
dark_hdr = self.get_envi_header_dict(self.get_hdr_filename(self.dark_file_path))
# dark_hdr = self.get_envi_header_dict(self.get_hdr_filename(self.dark_file_path))
dark_hdr = spectral.envi.read_envi_header(self.get_hdr_filename(self.dark_file_path))
# 重采样
f = interp1d(self.asd_radiance[:, 0], self.asd_radiance[:, 1])
# wave_destination = dn_hdr["wavelength"].removeprefix("{").removesuffix("}").split(",")
asd_radiance_interpolated = [f(float(i)) for i in dn_hdr["wavelength"]]
asd_radiance_interpolated2 = np.array(asd_radiance_interpolated)
notuse = np.zeros((asd_radiance_interpolated2.shape[0], 2))
notuse[:, 0] = np.array([float(i) for i in dn_hdr["wavelength"]])
notuse[:, 1] =asd_radiance_interpolated2
np.savetxt(os.path.join(self.out_file_path, "asd_radiance_interpolated.txt"), notuse)
# 将影像所有行平均，得到一行（帧）影像
img_data_ave = np.mean(self.img_data, axis=1)
@ -203,12 +227,11 @@ class RadianceCalibration():
# 去除暗电流
img_data_ave_rmdark = img_data_ave - img_dark_data_ave
img_dark_data_ave = img_dark_data_ave + 50
gain = np.empty((img_data_ave_rmdark.shape[0], 1, img_data_ave_rmdark.shape[1]))
offset = np.empty((img_data_ave_rmdark.shape[0], 1, img_data_ave_rmdark.shape[1]))
for i in range(gain.shape[2]):
gain[:, 0, i] = self.asd_radiance[:, 1] / img_data_ave_rmdark[:, i]
gain[:, 0, i] = asd_radiance_interpolated2 / img_data_ave_rmdark[:, i]
offset[:, 0, i] = img_dark_data_ave[:, i]
gain_name = os.path.join(self.out_file_path, "gain.bip")