将图像堆叠为numpy数组

Question

I'm trying to use a for-loop to stack 6 different images one on top of another to create a 3D stack.I'm new to Python...and I am not able to figure this out. How can I create the stack and how can I access each image in the stack later? My code is somewhat like this...

image = data.camera()

noisyImage = np.zeros(image.shape(0),image.shape(1))

fig = plt.figure(figsize=(12,4))  

for i in range(6):
    noisyImage = util.random_noise(image,mode='gaussian',seed=i)
    result = np.dstack(noisyImage,noisyImage)
    ax = plt.subplot(2,3,i)

Answer 1

Try this:

# reshape array that is (N,M) to one that is (N,M,1)   no increase in size happens.
n1=np.reshape(noisyImage,noisyImage.shape+(1,))
if(i==1):
    result=n1
else:
#   concatenate the N,M,1 version of the array to the stack using the third index (last index) as the axis.
    result=np.concatenate(result,n1,axis=n1.ndim-1)

---

The code below is a more general implementation (from which my answer above was taken) to apply a function designed to be applied to a single channel to all channels in the image.

def MatrixToMultiChannel(f,x,*args,**kwargs):
    nchannels=x.shape[-1]
    y=np.reshape(x,(x.size/nchannels,nchannels))
    for i in range(0,nchannels):
        yi=np.reshape(y[:,i],x.shape[:x.ndim-1])
        m1=genericF(f,yi,*args, **kwargs)
        m1=np.reshape(m1,m1.shape+(1,))
        if(i==0):
            fout=m1
        else:
            fout=np.concatenate((fout,m1),axis=m1.ndim-1)
    return fout