在Python中以全分辨率显示和保存大型2D矩阵

Question

I have a large 2D array (4000x3000) saved as a numpy array which I would like to display and save while keeping the ability to look at each individual pixels. For the display part, I currently use matplotlib imshow() function which works very well.

For the saving part, it is not clear to me how I can save this figure and preserve the information contained in all 12M pixels. I tried adjusting the figure size and the resolution (dpi) of the saved image but it is not obvious which figsize/dpi settings should be used to match the resolution of the large 2D matrix displayed. Here is an example code of what I'm doing (arr is a numpy array of shape (3000,4000)):

fig = pylab.figure(figsize=(16,12))
pylab.imshow(arr,interpolation='nearest')
fig.savefig("image.png",dpi=500)

One option would be to increase the resolution of the saved image substantially to be sure all pixels will be properly recorded but this has the significant drawback of creating an image of extremely large size (at least much larger than the 4000x3000 pixels image which is all that I would really need). It also has the disadvantage that not all pixels will be of exactly the same size.

I also had a look at the Python Image Library but it is not clear to me how it could be used for this purpose, if at all.

Any help on the subject would be much appreciated!

Answer 1

I think I found a solution which works fairly well. I use figimage to plot the numpy array without resampling. If you're careful in the size of the figure you create, you can keep full resolution of your matrix whatever size it has.

I figured out that figimage plots a single pixel with size 0.01 inch (this number might be system dependent) so the following code will for example save the matrix with full resolution (arr is a numpy array of shape (3000,4000)):

rows = 3000
columns = 4000
fig = pylab.figure(figsize=(columns*0.01,rows*0.01))
pylab.figimage(arr,cmap=cm.jet,origin='lower')
fig.savefig("image.png")

Two issues I still have with this options:

1. there is no markers indicating column/row numbers making it hard to know which pixel is which besides the ones on the edges
2. if you decide to interactively look at the image, it is not possible to zoom in/out

A solution that also solves the above 2 issues would be terrific, if it exists.

Answer 2

The OpenCV library was designed for scientific analysis of images. Consequently, it doesn't "resample" images without your explicitly asking for it. To save an image:

import cv2
cv2.imwrite('image.png', arr)

where arr is your numpy array. The saved image will be the same size as your array arr .

You didn't mention the color-model that you are using. Pngs, like jpegs, are usually 8-bit per color channel. OpenCV will support up to 16-bits per channel if you request it.

Documentation on OpenCV's imwrite is here .