spectral/ColorConvert

 
import cvb
import cvb.spectral
import numpy as np
import os
 
data_root = os.path.join(cvb.install_path(), "tutorial", "Spectral", "Images", "Leaf")
 
object_header = os.path.join(data_root, "leaf.hdr")
object_binary = os.path.join(data_root, "leaf.bin")
 
white_ref_header = os.path.join(data_root,"WRef.hdr")
white_ref_binary = os.path.join(data_root, "WRef.bin")
 
black_ref_header = os.path.join(data_root, "BRef.hdr")
black_ref_binary = os.path.join(data_root, "BRef.bin")
 
print("Load cube from:")
print("\t"+ str(object_header))
print("\t"+ str(object_binary))
print("White Refernce:")
print("\t"+ str(white_ref_header))
print("\t"+ str(white_ref_binary))
print("Black Refernce:")
print("\t"+ str(black_ref_header))
print("\t"+ str(black_ref_binary))
 
 
object_cube = cvb.spectral.Cube(object_header, object_binary)
white_ref = cvb.spectral.Cube(white_ref_header, white_ref_binary)
black_ref = cvb.spectral.Cube(black_ref_header, black_ref_binary)
 
cube_norm = cvb.spectral.normalize(object_cube, white_ref, black_ref, cvb.spectral.NormalizationMethod.AverageReferences1)
print("Normalization done!")
 
interpolator = cvb.spectral.Interpolator(cube_norm, cvb.spectral.StdObserver.CIE2006_2deg, cvb.spectral.StdIlluminant.D50, cvb.spectral.InterpolationMethod.Linear)
 
lab_image = cvb.spectral.convert_cube_to_lab(cube_norm, interpolator)
print("Lab calculation done!")
 
rgb_image = cvb.spectral.convert_lab_to_rgb8(lab_image, interpolator)
print("sRGB calculation done")
 
lab_image.save("LabImage.tiff")
rgb_image.save("RGBImage.tiff")