Monday, May 23, 2011

Making a MFISH image

The first trial with numpy was not very successful. After code simplification, I get a result:
RGB image combining five monospectral images
The code is:
# -*- coding: utf-8 -*-
"""
Created on Mon May 23 14:07:40 2011

@author: jean-pat
"""

import numpy as np
import os
import pylab
#from scipy import linalg as la
#from scipy import ndimage as nd
import scipy as sp
user=os.path.expanduser("~")
workdir=os.path.join(user,"Applications","ImagesTest","MFISH")
blue="Aqua.tif"
green="Green.tif"
gold="Gold.tif"
red="Red.tif"
frd="FarRed.tif"
complete_path=os.path.join(workdir,blue)
i1=sp.misc.imread(complete_path)
#
complete_path=os.path.join(workdir,green)
i2=sp.misc.imread(complete_path)
#
complete_path=os.path.join(workdir,gold)
i3=sp.misc.imread(complete_path)
#
complete_path=os.path.join(workdir,red)
i4=sp.misc.imread(complete_path)
#
complete_path=os.path.join(workdir,frd)
i5=sp.misc.imread(complete_path)

R=0.8*i5+0.15*i4+0.05*i3+0.00*i2+0.00*i1
V=0.00*i5+0.05*i4+0.05*i3+0.80*i2+0.10*i1
B=0.00*i5+0.00*i4+0.05*i3+0.15*i2+0.80*i1
shape=i5.shape
rgb = np.zeros((shape[0],shape[1],3),dtype=np.uint8)
rgb[:,:,0]=np.copy(R)
rgb[:,:,1]=np.copy(V)
rgb[:,:,2]=np.copy(B)
pylab.subplot(111,frameon=False, xticks=[], yticks=[])
pylab.imshow(rgb)
pylab.show()

I received new advices today
# -*- coding: utf-8 -*-
"""
Created on Mon May 23 14:07:40 2011

@author: jean-pat
"""

import numpy as np
import os
import pylab
#from scipy import linalg as la
#from scipy import ndimage as nd
import scipy as sp
user=os.path.expanduser("~")
workdir=os.path.join(user,"Applications","ImagesTest","MFISH")
blue="Aqua.tif"
green="Green.tif"
gold="Gold.tif"
red="Red.tif"
frd="FarRed.tif"
complete_path=os.path.join(workdir,blue)
i1=sp.misc.imread(complete_path)
#
complete_path=os.path.join(workdir,green)
i2=sp.misc.imread(complete_path)
#
complete_path=os.path.join(workdir,gold)
i3=sp.misc.imread(complete_path)
#
complete_path=os.path.join(workdir,red)
i4=sp.misc.imread(complete_path)
#
complete_path=os.path.join(workdir,frd)
i5=sp.misc.imread(complete_path)
######################
multi_spectr = np.dstack([i1,i2,i3,i4,i5])
conv_matrix = np.array([
[0.8,0.15,0.05,0,0],
[0,0.05,0.05,0.8,0.1],
[0,0,0.05,0.15,0.8]
])
 
shape = multi_spectr.shape
multi_spectr = multi_spectr.reshape(shape[0]*shape[1],shape[2])
rgb = np.dot(multi_spectr,conv_matrix.T).reshape(shape[:2]+(3,))
rgb8=np.uint8(rgb)
########################
#R=0.8*i5+0.15*i4+0.05*i3+0.00*i2+0.00*i1
#V=0.00*i5+0.05*i4+0.05*i3+0.80*i2+0.10*i1
#B=0.00*i5+0.00*i4+0.05*i3+0.15*i2+0.80*i1
#shape=i5.shape
#rgb = np.zeros((shape[0],shape[1],3),dtype=np.uint8)
#rgb[:,:,0]=np.copy(R)
#rgb[:,:,1]=np.copy(V)
#rgb[:,:,2]=np.copy(B)
pylab.subplot(111,frameon=False, xticks=[], yticks=[])
pylab.imshow(rgb8)
pylab.show()

That yields:

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