索引3D numpy数组

Question

I have an image that has 7 bands with 6938x752 pixels in each band. I want to do some processing on it so am using a python module called RIOS that deals with the reading and writing of the image to let the user focus on the processing. It reads the image in as a numpy array in blocks so that the processing is more efficient than reading in the whole image.

It reads the image in as a numpy array with the shape (7, 200, 200). I want to process the data by pixel so that I have the information from each band for each pixel. Is there a way to index the array so that for I can process just the 7 values (one for each band) for each pixel within image?

The only little code I can provide here is the function I use to read in, process and write the data.

def MASKimage(info, inputs, outputs):

    inputs.image1 = inputs.image1.astype(numpy.float32) # Read the image in as an array with shape (7, 200, 200)

    process = * Do some processing on the array which is the 7 values pixel by pixel * # has shape (1,7)

    outputs.outimage = process

Answer 1

You can try using np.transpose and np.reshape :

inputs.image1 = input.images1.transpose((1,2,0)).reshape(200*200,7)

You can just iterate through the image with a single loop to do your processing as each element represents a pixel with 7 bands.