I wanted to try out some simple operations on files and I started with opening and saving files (I use Python)
image = cv2.imread("image.png")
cv2.imwrite("image_processed.png", image)
After this operation my original image
from 33kB transforms into the same looking 144kB image.
I have tried doing something like this : http://opencv.itseez.com/modules/highgui/doc/reading_and_writing_images_and_video.html?highlight=imwrite#imwrite
params = list()
params.append(cv.CV_IMWRITE_PNG_COMPRESSION)
params.append(8)
image = cv2.imread("image.png")
cv2.imwrite("image_processed.png",image,params)
But this does not change much ( size decreased to 132kB )
This is the image which I am working with:
Semi-related, but I had the same issue with
matplotlib.image.imsave
- it would save an 8-bit grayscale image as 16-bit, which ballooned the size, even after usingscipy.misc.bytescale
to make sure it was an 8-bit array. However,scipy.misc.imsave
saved it correctly as an 8-bit image.As hinted by ypnos, your source file is jpg (even if it has the png extension). That is why, when you save it in png format, it will use more space, as you are changing the format (jpg to png).
Try replacing the last line with:
And you will see that the size doesn't change that much.
Alternatively, keep the code as it is, but use a different image, such as http://upload.wikimedia.org/wikipedia/commons/4/47/PNG_transparency_demonstration_1.png
You can use a third-party command line tool optipng to re-compress and shrink the png file size without losing anything.
Reference:
http://optipng.sourceforge.net/pngtech/optipng.html
https://github.com/johnpaulada/optipng
Some png writers like GIMP write much better compressed PNGs than standard libpng, which is used by opencv. You can also open and save the image again with Imagemagick, and see what difference that makes (as compared to OpenCV).
There is even specialized software that tries to better re-compress PNGs, like pngcrush.
Can you provide the image in question? I would like to play with it, regarding file size optimization.