import os
import numpy as np
from polsartools.utils.utils import conv2d,time_it
from osgeo import gdal
gdal.UseExceptions()
import matplotlib.pyplot as plt
from .pauliRGB import generate_rgb_png, create_pgw, generate_rgb_tif, norm_data, read_bin #create_prj
[docs]
@time_it
def dxpRGB(infolder, type=1, save_tif=False, window_size=None):
"""
Generate false-color RGB visualization from dual-polarimetric Sxy, C2 SAR data.
This function creates an RGB image from dual-pol (Sxy, C2) matrix inputs.
Examples
--------
>>> # Generate type-1 false-color RGB from C2 folder
>>> dxpRGB("/path/to/data")
>>> # Output both PNG and GeoTIFF versions
>>> dxpRGB("/path/to/data", type=3, tif_flag=True)
Parameters
----------
infolder : str
Path to the input folder containing C2 matrix components (C11, C22, C12_real).
type : int, {1, 2, 3, 4}, default=1
RGB combination type:
- 1: Blue=C11, Red=C22, Green=|C11 + C22 - 2·C12_real|
- 2: Blue=C22, Red=C11, Green=|C11 + C22 - 2·C12_real|
- 3: Blue=C11, Red=C22, Green=|C11 - C22|
- 4: Blue=C22, Red=C11, Green=|C22 - C11|
save_tif : bool, default=False
If True, generates a GeoTIFF (.tif) file alongside the PNG image.
Returns
-------
None
Writes RGB visualization to disk:
- 'RGB#.png': False-color PNG image (with world file for georeferencing)
- 'RGB#.tif': Optional GeoTIFF output if `tif_flag=True`
"""
def find_file(base):
for ext in [".bin", ".tif"]:
path = os.path.join(infolder, f"{base}{ext}")
if os.path.isfile(path):
return path
return None
c11_path = find_file("C11")
c22_path = find_file("C22")
c12r_path = find_file("C12_real")
if c11_path and c22_path:
C11 = read_bin(c11_path)
C22 = read_bin(c22_path)
C12 = read_bin(c12r_path) if c12r_path else None
else:
# Try all valid input combos
combinations = [
("s11", "s12"),
("s11", "s21"),
("s22", "s12"),
("s22", "s21"),
]
for sA, sB in combinations:
pathA = find_file(sA)
pathB = find_file(sB)
if pathA and pathB:
S1 = read_bin(pathA).astype(np.complex64)
S2 = read_bin(pathB).astype(np.complex64)
# Construct C11, C22, C12
C11 = (np.abs(S1) ** 2).astype(np.float32)
C22 = (np.abs(S2) ** 2).astype(np.float32)
C12 = (S1 * np.conj(S2)).astype(np.complex64)
break
else:
raise FileNotFoundError("No valid C2 or Sxy data found. Expected one of: (s11,s12), (s11,s21), (s22,s12), (s22,s21) (C11,C22,C12_real)")
# Compute RGB channels
if type == 1:
red = norm_data(C22)
blue = norm_data(C11)
green = norm_data(np.abs(C11 + C22 - 2 * C12.real))
elif type == 2:
red = norm_data(C11)
blue = norm_data(C22)
green = norm_data(np.abs(C11 + C22 - 2 * C12.real))
elif type == 3:
red = norm_data(C22)
blue = norm_data(C11)
green = norm_data(np.abs(C11 - C22))
elif type == 4:
red = norm_data(C11)
blue = norm_data(C22)
green = norm_data(np.abs(C22 - C11))
else:
raise ValueError("Invalid type!! Valid types are 1,2,3,4")
if c11_path:
georef_file = c11_path
else:
georef_file = pathA # Use the first file for georeferencing
output_path = os.path.join(infolder, f'RGB{type}.png')
if window_size is not None:
kernel = np.ones((window_size, window_size), np.float32) / (window_size * window_size)
red = conv2d(red, kernel).astype(np.float32)
green = conv2d(green, kernel).astype(np.float32)
blue = conv2d(blue, kernel).astype(np.float32)
generate_rgb_png(red, green, blue, georef_file, output_path)
create_pgw(georef_file, output_path)
print(f"RGB image saved as {output_path}")
if save_tif:
tif_path = os.path.join(infolder, f'RGB{type}.tif')
generate_rgb_tif(red, green, blue, georef_file, tif_path)
print(f"RGB GeoTIFF saved as {tif_path}")
@time_it
def dxpRGB_old(infolder, type = 1 , save_tif = False):
"""
Generate false-color RGB visualization from C2 dual-polarimetric SAR data.
This function creates an RGB image from dual-pol (C2) covariance matrix inputs
to enhance polarimetric contrast through various combinations of C11, C22, and
C12_real. The output provides a quick-look visualization useful for interpreting
scattering mechanisms and surface features.
Examples
--------
>>> # Generate type-1 false-color RGB from C2 folder
>>> dxpRGB("/path/to/C2_data")
>>> # Output both PNG and GeoTIFF versions
>>> dxpRGB("/path/to/C2_data", type=3, tif_flag=True)
Parameters
----------
infolder : str
Path to the input folder containing C2 matrix components (C11, C22, C12_real).
type : int, {1, 2, 3, 4}, default=1
RGB combination type:
- 1: Blue=C11, Red=C22, Green=|C11 + C22 - 2·C12_real|
- 2: Blue=C22, Red=C11, Green=|C11 + C22 - 2·C12_real|
- 3: Blue=C11, Red=C22, Green=|C11 - C22|
- 4: Blue=C22, Red=C11, Green=|C22 - C11|
save_tif : bool, default=False
If True, generates a GeoTIFF (.tif) file alongside the PNG image.
Returns
-------
None
Writes RGB visualization to disk:
- 'RGB#.png': False-color PNG image (with world file for georeferencing)
- 'RGB#.tif': Optional GeoTIFF output if `tif_flag=True`
"""
def find_file(prefix):
for ext in [".bin", ".tif"]:
path = os.path.join(infolder, f"{prefix}{ext}")
if os.path.isfile(path):
return path
return None
c11_path = find_file("C11")
c22_path = find_file("C22")
c12r_path = find_file("C12_real")
if c11_path and c22_path:
C11 = read_bin(c11_path)
C22 = read_bin(c22_path)
C12r = read_bin(c12r_path) if c12r_path else None
if type == 1:
blue = norm_data(C11)
red = norm_data(C22)
green = norm_data(np.abs(C11 + C22 - 2 * C12r))
elif type == 2:
blue = norm_data(C22)
red = norm_data(C11)
green = norm_data(np.abs(C11 + C22 - 2 * C12r))
elif type == 3:
blue = norm_data(C11)
red = norm_data(C22)
green = norm_data(np.abs(C11 - C22))
elif type == 4:
blue = norm_data(C22)
red = norm_data(C11)
green = norm_data(np.abs(C22 - C11))
else:
raise ValueError("Invalid type!! Valid types are 1,2,3,4")
georef_file = c11_path
output_path = os.path.join(infolder, f'RGB{type}.png')
generate_rgb_png(red, green, blue,georef_file, output_path)
create_pgw(georef_file, output_path)
# create_prj(georef_file, output_path)
print(f"RGB image saved as {output_path}")
if save_tif:
output_path = os.path.join(infolder, f'RGB{type}.png')
generate_rgb_tif(red, green, blue, georef_file, output_path)
print(f"RGB image saved as {output_path}")
else:
raise ValueError("Invalid C2 folder!!")
