I have an image with a transparent background, but when I open it in MATLAB, I get a black background. I'm overlaying it on top of a background image. How can I get this to display? I've tried using the alpha function alpha(image,0) but it sets my entire image to 0. Is it possible for me to set the alpha of individual pixels to be equal to 0? That way I can run each pixel through a loop.
I'm not sure if this helps, but when I run a imfinfo('ryu1.png'), I get :
...
Transparency = 'alpha'
SimpleTransparencyData = []
...
You can read in your image using imread. However, you need to specify additional output parameters if you want to grab the alpha channel. You need to call it like this:
[im, map, alpha] = imread('ryu1.png');
im is your image read in, map is the colour map which we will ignore, but alpha contains the transparency information that you want. First call imshow and record the handle to the image, then set your transparency with the alpha channel using the set command. In other words:
[im, map, alpha] = imread('ryu1.png');
f = imshow(im);
set(f, 'AlphaData', alpha);
This should make the figure with the transparency intact.
Addition (Thanks to Yvon)
Supposing you already have a background image loaded into MATLAB. If you want to blend these two together, you need to do some alpha matting. You use the alpha channel and mix the two together. In other words, supposing your background image is stored in img_background and img_overlay is the image you want to go on top of the background, do this:
alphaMask = im2double(alpha); %// To make between 0 and 1
img_composite = im2uint8(double(img_background).*(1-alphaMask) + double(img_overlay).*alphaMask);
The first step is necessary as the alpha map that is loaded in will be the same type as the input image, which is usually uint8. We need to convert this to a double image such that it goes in between 0 and 1, and im2double is perfect to do this. The second line converts each of the images to double precision so that we can compute this sum and in order to make the data types between the alpha mask and both images are compatible. We then convert back to uint8. You can then show this final image using imshow.
Related
I am trying to get the hue, saturation and value images from an image (originally colored). I converted the image using the rgb2hsv() function but I am confused on how to get the component images.
As Matlab mentions, the output of rgb2hsv is returned as an m-by-n-by-3 image array whose three planes contain the hue, saturation, and value components of the image.Therefore you can simply get these components as:
hsv_image = rgb2hsv(rgb_image);
hue_component= hsv_image(:,:,1);
saturation_component= hsv_image(:,:,2);
value _component= hsv_image(:,:,3);
I am trying to understand why I am not getting expected result from the following lines of code:
pix=np.asarray(Image.open(File))) #I am reading a pbm file into memory
img = Image.fromarray((pix), '1') #rewriting
img.save("test1.pbm")
newpix=~pix #inverting the image
img = Image.fromarray((newpix), '1')
img.save("test2.pbm")
original image and test1.pbm(image 1) is same, but test2.pbm (image 2) isn't what I am expecting (the foreground pixels become background ones and vice versa). I am attaching the images here (converted to jpeg). What am I doing wrong?
Another issue is that for most of the foreground pixels in test1.pbm, the value is False. But that is not reflected in the saved image.
I converted both of these images from this original image http://www.mathgoodies.com/lessons/graphs/images/line_example1.jpg using Imagemagick.
I don't recognise which language you are using, but your original image, when converted with ImageMagick like this:
convert cdLTY.jpg -negate out.jpg
looks like this:
So I deduce the problem is in your inversion. I don't know what
newpix=~pix
does (probably complelementing it or inverting all the bits?) but I think you need to subtract each pixel from 255 to invert your image, so if a pixel is 10 in the original image, it needs to be 255-10 or 245 in the new image.
Explanation
Pixels are normally encoded with 0=black and 255=white. So, if your pixel was originally black (0) when you do new pixel = 255 - original value, it will become 255-0, or 255 meaning it is now white. Likewise, if a pixel starts off white (255), when you do 255-255 you get 0 which is now black.
I have grayscale satellite image which is processed from spectral data (band classifications). If i use jet colormap in imshow it will show absolute colormapped image. But if i try to imwrite in particular place it is saved like a bluish image. I saw one example in matlab central, but i didnt get. can anyone help me to write my image with colorscaled image.
Matlab central link: http://www.mathworks.in/matlabcentral/answers/25026-saving-grayscale-image-as-it-appears-in-jet-colormap-of-imagesc
there accepted answer link is : http://www.mathworks.com/matlabcentral/fileexchange/7943
I have tried many times, this will show colormaped images in plots (imshow) they didnt write anywhere with colormaped. Now i want to write my image with colormaped.
example code:
I= imread('image path');
imshow(I,'colormap',jet);
imwrite(I,'path','jpg'); /not working
or
imwrite(I,jet,'path','jpg'); /not working
Please help to solve this issue.
When you use imshow the colormap is always adjusted to the range of values in your image. imwrite however assumes your image has a value range of [0,1] if you are using single or double data types. Try to scale your image to the range [0,1] before saving.
If you provide a colormap in the call to imwrite, MATLAB assumes you are using an indexed image. Thus you will have to convert the image to the indexed format first. The following snippet worked for a test image I of mine:
% scale to [0,1]
I = I - min(I(:));
I = I ./ max(I(:));
% Create indexed image
[J,~] = gray2ind(I);
% Save image
imwrite(J,jet,'path','jpg');
Solution by hbaderts worked well for me, but later I found out that some images were still scaled slightly different way from imshow.
However, I might found a reason of an original problem. Just after Matlab starts, its default colormaps (including 'jet') are set to 64 colors (64x3). Then, if any image is shown with a colormap, for example if imshow('cameraman.tif'), colormap('jet') is executed, all default colormaps become 256x3 (can be verified with jetMap=jet; before and after). Then it might happen that an image was written with a colormap different from the one applied to image figure (for example, if a figure called after imwrite).
Finally I found this solution (no image pre-scaling needed):
% Create indexed image, explicitly using 256 colors
imInd=gray2ind(im,256);
% Convert indexed image to RGB using 256-colors jet map
jetRGB=ind2rgb(imInd,jet(256));
% Save image
imwrite(jetRGB,'jet.png');
The images I used have the same color scale now, both the saved one and the one shown in figure.
I noticed that when displaying jpg or png images they look alot like a GIF file in that there is limited colors and "banding".
You can see the original and a screenshot attached. Kinda hard to tell scaled down but you can see it.
Actually better example. See the banding around the circle?
Here is my code:
#pygame code to render an image
import pygame, os
import time
image = 'gradient-test.png' #located in same folder as this file:resized in Photoshop
pygame.init() #I assume you did this?
SCREEN = pygame.display.set_mode((1366, 768))
pygame.mouse.set_pos((1366, 768))
picture = pygame.image.load(image)
SCREEN.blit(picture,(0,0))
pygame.display.update()
time.sleep(5)
It seems like a problem with the pixel format of your surface. You can add the following lines to your script to see if there's a difference between the pixel format of your image surface and your screen surface:
print 'picture', picture.get_bitsize()
print 'screen', SCREEN.get_bitsize()
It's good practice and recommended to always change the pixel format of any new surface to the pixel format of your screen surface by calling convert():
convert()
change the pixel format of an image
convert(Surface) -> Surface
Creates a new copy of the Surface with the pixel format changed ...
If no arguments are passed the new Surface will have the same pixel format as the display Surface. This is always the fastest format for blitting. It is a good idea to convert all Surfaces before they are blitted many times.
It's simple:
picture = pygame.image.load(image).convert() # added convert() call
Also, you can try to set the color depth of your screen manually, like:
SCREEN = pygame.display.set_mode((1366, 768),0, 32) # use 32-bit color depth
I use the below command to display the image
imshow(img,[]);
when i use the following command to save the image it is saved as an empty white page
imsave;
how to save the image in this case any command would do
You are probably running into an issue with matrix type and range. If img is type double it needs to be scaled between 0 and 1.
A common issue is to load an image in uint8 (scaled between 0 and 255), convert to double in order to do some processing on it, without scaling, and then try and save it out. When you do that, MATLAB tries to convert back to uint8, and any values in the image outside the [0 1] range are clipped. On many images this means that the file comes out all white.
To get around this, use functions like im2double and im2uint8 rather than just double or uint8 when converting images.
Try at the command line the difference between:
img = imread('pout.tif');
img = double(img);
imshow(img,[]);
imsave;
and
img = imread('pout.tif');
img = im2double(img);
imshow(img,[]);
imsave;
Convert image data into an actual image and try again:
h = image(img); %Convert to object
imsave(h); %Save image object
Notice that if you close the figure window generated by image(), the object is deleted and the handle has will point to nothing. Though this may be beyond of what you are asking for.
Hope this adjustment solved your problem
First convert the image to rgb using
img1=label2rgb(img);
then again convert the image into an gray image using
img2=rgb2gray(img1);
then u can use imshow to show the image and save it using imsave
imshow(img2);
imsave();