I am writing a function that generates a movie mimicking a particle in a fluid. The movie is coloured and I would like to generate a grayscaled movie for the start. Right now I am using avifile instead of videowriter. Any help on changing this code to get grayscale movie? Thanks in advance.
close all;
clear variables;
colormap('gray');
vidObj=avifile('movie.avi');
for i=1:N
[nx,ny]=coordinates(Lx,Ly,Nx,Ny,[x(i),-y(i)]);
[xf,yf]=ndgrid(nx,ny);
zf=zeros(size(xf))+z(i);
% generate a frame here
[E,H]=nfmie(an,bn,xf,yf,zf,rad,ns,nm,lambda,tf_flag,cc_flag);
Ecc=sqrt(real(E(:,:,1)).^2+real(E(:,:,2)).^2+real(E(:,:,3)).^2+imag(E(:,:,1)).^2+imag(E(:,:,2)).^2+imag(E(:,:,3)).^2);
clf
imagesc(nx/rad,ny/rad,Ecc);
writetif(Ecc,i);
if i==1
cl=caxis;
else
caxis(cl)
end
axis image;
axis off;
frame=getframe(gca);
cdata_size = size(frame.cdata);
data = uint8(zeros(ceil(cdata_size(1)/4)*4,ceil(cdata_size(2)/4)*4,3));
data(1:cdata_size(1),1:cdata_size(2),1:cdata_size(3)) = [frame.cdata];
frame.cdata = data;
vidObj = addframe(vidObj,frame);
end
vidObj = close(vidObj);
For your frame data, use rgb2gray to convert a colour frame into its grayscale counterpart. As such, change this line:
data(1:cdata_size(1),1:cdata_size(2),1:cdata_size(3)) = [frame.cdata];
To these two lines:
frameGray = rgb2gray(frame.cdata);
data(1:cdata_size(1),1:cdata_size(2),1:cdata_size(3)) = ...
cat(3,frameGray,frameGray,frameGray);
The first line of the new code will convert your colour frame into a single channel grayscale image. In colour, grayscale images have all of the same values for all of the channels, which is why for the second line, cat(3,frameGray,frameGray,frameGray); is being called. This stacks three copies of the grayscale image on top of each other as a 3D matrix and you can then write this frame to your file.
You need to do this stacking because when writing a frame to file using VideoWriter, the frame must be colour (a.k.a. a 3D matrix). As such, the only workaround you have if you want to write a grayscale frame to the file is to replicate the grayscale image into each of the red, green and blue channels to create its colour equivalent.
BTW, cdata_size(3) will always be 3, as getframe's cdata structure always returns a 3D matrix.
Good luck!
Related
I have a 4-channel image (.png, .tif) like this one:
I am using OpenCV, and I would like to add padding of type BORDER_REFLECT around the flower. copyMakeBorder is not useful, since it adds padding to the edges of the image.
I can add certain padding if I split the image in bgr + alpha and apply dilate with BORDER_REFLECT option on the bgr image, but that solution spoils all the pixels of the flower.
Is there any way to perform a selective BORDER_REFLECT padding addition on a ROI defined by a binary mask?
EDIT:
The result I expect is something like (sorry I painted it very quickly with GIMP) :
I painted two black lines to delimit the old & new contour of the flower after the padding, but of course those lines should not appear in the final result. The padding region (inside the two black lines) must be composed by mirrored pixels from the flower (I painted it yellow to make it understandable).
A simple python script to resize the image and copy the original over the enlarged one will do the trick.
import cv2
img = cv2.imread('border_reflect.png', cv2.IMREAD_UNCHANGED)
pad = 20
sh = img.shape
sh_pad = (sh[0]+pad, sh[1]+pad)
imgpad = cv2.resize(img, sh_pad)
imgpad[20:20+sh[0], 20:20+sh[1], :][img[:,:,3]==255] = img[img[:,:,3]==255]
cv2.imwrite("padded_image.png", imgpad)
Here is the result
But that doesn't look very 'centered'. So I modified the code to detect and account for the offsets while copying.
import cv2
img = cv2.imread('border_reflect.png', cv2.IMREAD_UNCHANGED)
pad = 20
sh = img.shape
sh_pad = (sh[0]+pad, sh[1]+pad)
imgpad = cv2.resize(img, sh_pad)
def get_roi(img):
cimg = img[:,:,3].copy()
contours,hierarchy = cv2.findContours(cimg,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
#Remove the tiny pixel noises that get detected as contours
contours = [cnt for cnt in contours if cv2.contourArea(cnt) > 10]
x,y,w,h = cv2.boundingRect(cnt)
roi=img[y:y+h,x:x+w]
return roi
roi = get_roi(img)
roi2 = get_roi(imgpad)
sh = roi.shape
sh2 = roi2.shape
o = ((sh2[0]-sh[0])/2, (sh2[1]-sh[1])/2)
roi2[o[0]:o[0]+sh[0], o[1]:o[1]+sh[1], :][roi[:,:,3]==255] = roi[roi[:,:,3]==255]
cv2.imwrite("padded_image.png", imgpad)
Looks much better now
The issue has been already addressed and solved here:
http://answers.opencv.org/question/90229/add-padding-to-object-in-4-channel-image/
I'm trying to combine the two images based on the information from the mask. I'm using the color information from the background image if the mask is 0 and color information from foreground image if the mask is 1. Because the mask and both
Images are of the same size, I would like to use logical indexing of matrices to achieve this.
My attempt:
mask = imread('mask.png');
foreground = imread('fg.jpg');
background = imread('bg.jpg');
[r,c,~]=size(mask);
A = zeros(size(mask));
for i=1:r
for j=1:c
if mask(i,j) == 0
A(i,j,:) = background(i,j,:);
end
if mask(i,j) > 0
A(i,j,:) = foreground(i,j,:);
end
end
end
imshow(A);
The result looks like a flickering blue image, but I don't want that. Please help.
You can do this a bit more concisely:
f = double(foreground).*double(mask);
b = double(background).*double(~mask);
blend = f+b;
imshow(blend, []);
Using logical indexing you could also do
foreground(logical(mask)) = 0;
background(logical(~mask)) = 0;
blend = foreground+background;
The ISNOT operator '~' inverts your matrix in the second line, so you cut out the area you would like for background.
NOTE: This works for black and white (one channel). For coloured images see rayryeng's solution.
There are two problems with your code. The first problem is that you are trying to assign colour pixels to the output image A, yet this image is only two-dimensional. You want an image with three channels, not two. In addition, the output image type you are specifying is wrong. By default, the output image A is of type double, yet you are copying values into it that aren't double... most likely unsigned 8-bit integer.
As such, cast the image to the same type as the input images. Assuming both input images are the same type, initialize your A so that:
A = zeros(size(foreground), class(foreground));
This correctly makes a colour image with the same type as any of the inputs, assuming that they're both the same type.
Now, your for loop is fine, but it's better if you do this in one shot with logical indexing. If you want to use logical indexing, create a new image that's initially blank like what you've done, but then make sure your mask has three channels to match the number of channels the other images have. After, you simply need to index into each image and set the right locations accordingly:
mask = imread('mask.png');
foreground = imread('fg.jpg');
background = imread('bg.jpg');
[r,c,d]=size(mask); %// Change
%// If your mask isn't three channels, make it so
%// Change
if d ~= 3
mask = cat(3, mask, mask, mask);
end
A = zeros(size(foreground), class(foreground)); %// Change
A(mask) = foreground(mask); %// Assign pixels to foreground
A(~mask) = background(~mask); %// Assign pixels to background
imshow(A);
I am modifying images in matlab and I have a problem.
I need to separate the 3 channels of color and modify them separately.
I use this to obtain the three channels:
a = imread('./images/penguins.png');
colorlist = {'R','G','B'};
subplot(2,2,1);
imshow(a);
for k=1:3
subplot(2,2,k+1);
imshow( a(:,:,k));
title(colorlist{k});
end
a(:,:,k) is one color of the three. The problem is when I add the three vectors in one, to obtain the color image. I do this:
A=a(:,:,1)+a(:,:,2)+a(:,:,3)
figure; imshow(A);
But it dont works, it only show me a very highlight image, no a color image.
Anyone knows how can I recover the color image? Thanks for yout help^^
You are adding the values of the three layers instead of concatenating them in a 3D array.
Try this:
A= cat(3, a(:,:,1), a(:,:,2), a(:,:,3));
I should also note that you can edit the layers simply by indexing, say you want to switch the red and green components:
I1 = imread('http://i.stack.imgur.com/1KyJA.jpg');
I2=I1;
I2(:,:,1)=I1(:,:,2);
I2(:,:,2)=I1(:,:,1);
imshowpair(I1,I2, 'montage');
Now if I take your title literally, let's say you do want to add the three layers and display the result with a colormap, you can do:
A=a(:,:,1)+a(:,:,2)+a(:,:,3)
imagesc(A); axis image;
colorbar;
Results:
I want to decompose an image to Y,Cb,Cr components and then to perform downsampling in YCbCr domain to form the 4:2:2 format.
Code for decomposition of the image to YCbCr:
img=imread('flowers.tif');
figure(1), imshow(img);title('original image');
Y=0.299*img(:,:,1)+0.587*img(:,:,2)+0.114*img(:,:,3);
Cb=-0.1687*img(:,:,1)-0.3313*img(:,:,2)+0.5*img(:,:,3)+128;
Cr=0.5*img(:,:,1)-0.4187*img(:,:,2)-0.0813*img(:,:,3)+128;
%print Y, Cb, Cr components
figure(2), subplot (1,3,1), imshow(Y), title('Y,Cb,Cr components'),
subplot(1,3,2), imshow(Cb),subplot(1,3,3), imshow(Cr);
Now what i need to do to perform the down-sampling?
If by downsampling you specifically mean Chroma subsampling from 4:4:4 to 4:2:2, then one way to do it (and keep the original size of the channel) is to manually overwrite every other pixel with the previous value:
Cb(:, 2:2:end) = Cb(:, 1:2:end-1);
Cr(:, 2:2:end) = Cr(:, 1:2:end-1);
If you simply want to remove half of the columns, use:
Cb(:, 2:2:end) = [];
Cr(:, 2:2:end) = [];
Also in Matlab you don't need to write your own function for YCbCr conversion. Instead you can use rgb2ycbcr().
I have a grayscale image that only has the values 60 and 117. How can I convert the image to only black and white without graylevels?
I tried the matlab function gray2ind, but didn't get the expected output.
Thanks.
Try im2bw(img, level) with level = 0.5.
This is a matlab function that takes a grayscale image img, applies a threshold of level (a value between [0,1]) and returns a black and white image.
This function is part of the Image Processing Toolbox. Your case is simple enough that you could also try something like:
bwImg = false(size(img));
bwImg(img == 117) = true;
I edited the above to set values equal to false/true to more closely mimic Matlab's im2bw() which returns a matrix of logical values rather than ints.
2nd Edit: Modified the code block to reflect improvements suggested by #Amro