# Read reference image
ReferenceName = args.reference[i]
print '================================================================'
print 'Processing image : ', ReferenceName
# Read NIFTI
ReferenceNifti = sitk.ReadImage(ReferenceName)
# Get data from NIFTI
ReferenceImage = np.swapaxes(sitk.GetArrayFromImage(ReferenceNifti),0,2).astype('float32')
# Get resolution to scaling factor
UpScale = tuple(itemb/itema for itema,itemb in zip(ReferenceNifti.GetSpacing(),NewResolution))
# Modcrop to scale factor
ReferenceImage = modcrop3D(ReferenceImage,UpScale)
# ===== Generate input LR image =====
# Blurring
BlurReferenceImage = scipy.ndimage.filters.gaussian_filter(ReferenceImage,
sigma = SigmaBlur)
print 'Generating LR images with the resolution of ', NewResolution
# Downsampling
LowResolutionImage = scipy.ndimage.zoom(BlurReferenceImage,
zoom = (1/float(idxScale) for idxScale in UpScale),
order = 0)
# Normalization by the max valeur of LR image
MaxValue = np.max(LowResolutionImage)
ReferenceImage = np.swapaxes(sitk.GetArrayFromImage(ReferenceNifti), 0,
2).astype('float32')
# Normalization
ReferenceImage = imadjust3D(ReferenceImage, [0, 1])
# ===== Generate input LR image =====
# Blurring
BlurReferenceImage = scipy.ndimage.filters.gaussian_filter(
ReferenceImage, sigma=args.sigma)
for scale in args.scale:
print 'With respect to scale factor x', scale, ' : '
# Modcrop to scale factor
BlurReferenceImage = modcrop3D(BlurReferenceImage, scale)
ReferenceImage = modcrop3D(ReferenceImage, scale)
# Downsampling
LowResolutionImage = scipy.ndimage.zoom(
BlurReferenceImage,
zoom=(1 / float(idxScale) for idxScale in scale),
order=args.order)
# Cubic Interpolation
InterpolatedImage = scipy.ndimage.zoom(LowResolutionImage,
zoom=scale,
order=args.order)
# Shave border
LabelImage = shave3D(ReferenceImage, border)