This blog illustrates some simple stuff to deal with, when the images need to be saved with certain constraints.
Let’s start with simple text figure that needs to be saved in image format.
figure,axis off;
text(0.35,0.5,'\color[rgb]{red} E \color[rgb]{green}=\color[rgb]{blue} mc^2','FontSize',60,'FontName','Times New Roman','FontAngle','italic');
To save the above figure with different background:
The default background color is set to white in MATLAB. In order to have the different background color as in the figure, select ‘Export Setup’ in the figure window and select ‘Rendering’ from properties then unselect the custom color and finally select ‘Apply to figure’. Then select ‘Save As’ to save the image.
The step by step screenshots are as given below:
The final image saved in the local directory is as shown below.
To save the figure with black color background:
Select the custom color and type ‘k’ in the text box and select ‘Apply to figure’.
For Red, type ‘r’ or [1,0,0]. For Blue , type ‘b’ or [0,0,1]. For Green, type ‘g’ or [0 ,1,0]; For cyan ‘c’ or [0.5,1,1] and so on.
NOTE: ‘r’ denotes red color or a 1 x 3 Vector representing [R,G,B] can be used. The value ranges between 0 and 1. [1,0,0] denotes value of red component is 1 whereas Green and Blue components are zero. In other words, the color Red is chosen.
The final image saved in the local directory is as shown below.
Example 2:
A=imread('cameraman.tif');
figure,imagesc(A);colormap(jet);
To save the image without the padded white space:
Select ‘Export Setup’ from File in the figure window and select ‘Size’ from properties, type the width and height of the imageand change the units to ‘points’. Select ‘Expand the axes to fill figure’ checkbox and finally select ‘Apply to figure’ to view the changes.
This tutorial will come in handy if you are interested in learning about video processing using MATLAB. Techniques such as Reading and writing a video file, displaying the frames and writing the frames as images in a folder are discussed below.
To read a video file:
Vptr = VideoReader('VIDE01.mp4')
‘VideoReader’ command in MATLAB creates reader object for the video file. This object contains the metadata or the parameters related to the video such as Frame rate, Height and Width of the frames,duration of the video etc.
To read all the frames in the video, we can use two methods. The first method is to find the number of frames in the video and read it. The second method is to read the frames until no more video frames are available. Here in the tutorial, the frame rate is assumed to be constant throughout the duration of the video. At constant frame rate, the number of frames in the video is obtained by direct multiplication of frame rate and video duration. In our example, the video is 13.29 seconds long and the frame rate is 24.0. Multiplying 13.29 and 24 gives 318.96 that is 319 frames available in the video.
1. To Read the frames in the video , display , save as image file and store as mat file
EXAMPLE : 1
%MATLAB CODE:
Vptr = VideoReader('VIDE01.mp4');
%Num_Frames = Vptr.NumberOfFrames;
NFrames = round(Vptr.FrameRate*Vptr.Duration);
%Find the height and weight of the frame
Nrows = Vptr.height;
Ncols = Vptr.width;
%Preallocate the matrix
Img_s = zeros([Nrows,Ncols,NFrames]);
for i = 1:NFrames
%Read each frame
Img = readFrame(Vptr);
%To display all the frames
figure,imshow(Img);
%To save the images
Img_name=['Image',num2str(i),'.jpg'];
imwrite(Img,Img_name);
%To store in MAT file
Img_s(:,:,i)=Img;
end
%Save the matrix as .mat file
Save Video_Images.mat Img_s;
EXPLANATION:
The above MATLAB code can
a. Display all the frames in the video
b. Save all the frames as images in the current working directory
c. Store all the frames as images in a multidimensional matrix and save it as ‘.mat’ file
After creating the video reader object, the number of frames is computed using the frame rate and duration of the video. The height and width of the frame can be obtained from the metadata.
‘readFrame’ extracts each frame sequentially in the image format. The image can be further displayed using ‘imshow’ or written to an image file using ‘imwrite’ command or stored in a multidimensional matrix as stack of images.
The name format of the images saved in the current working directory will be ‘Image1.jpg’,’Image2.jpg’…’Image319.jpg’
2. To read all the frames in the video and display few frames
EXAMPLE 2:
%MATLAB CODE
Vptr = VideoReader('VIDE01.mp4');
NFrames = round(Vptr.FrameRate*Vptr.Duration);
Jump_ptr = 27;
N = 1;
%To display the Images
for i=1:NFrames
Img = readFrame(Vptr);
if(mod(i-1,Jump_ptr)==0)
figure(2),subplot(3,4,N),imshow(Img);
N=N+1;
end
end
EXPLANATION:
The above MATLAB code reads all the frames in the video but displays only few frames. This example typically highlights the use of MATLAB command ‘subplot’.
Instead of displaying all the frames, frames with specific interval are displayed. In this instance,frame 1 will be displayed first, frame 28 the next then followed by 55 and so on and so forth. ‘mod’ command is used to find the remainder after division, so whenever ‘i’ assumes the value equal to multiples of the variable ‘Jump_ptr’ then the image will be displayed. To displayall the images in the same figure, ‘subplot’ can be used.
‘subplot(3,4,N)’ refers that the ‘figure(2)’ can be divided into 3 rows and 4 columns and each image can be placed in each position. In the given example, number of frames =319 and the interval distance (Jump_ptr) is 27, then 319/27 gives 12. So the subplot is divided as 3 rows and 4 columns to allocate spacefor 12 images.
3. To read from a video file and write the frames to another video file
%To write frames to the video
Vptr = VideoReader('VIDE01.mp4');
Wptr = VideoWriter('VIDE02.mp4','MPEG-4');
Wptr.FrameRate=10;
open(Wptr);
for i=1:120
Img = readFrame(Vptr);
writeVideo(Wptr,Img);
end
close(Wptr);
EXPLANATION:
Create the video reader object using ‘VideoReader’ for ‘VIDEO1.mp4’
Create the video writer object using ‘VideoWriter’ for ‘VIDEO2.mp4’
Set the frame rate for the video to be written to a file.
Here, the frame rate 10 indicates,10 frames will be displayed per second in a video.
‘open’ command will open the video file to start the writing process. Instead of 319 frames from the original video(‘VIDEO1.MP4’), only 120 frames are written to the video file.So it is unnecessary to go through all the frames in the video. First read the frame from the input video file and write it to the output video file. After 120 frames are read from the input file and written to the output file, the output file is closed.
4. To read a video file and process the frames and write it to another video file
%To write frames to the video
%Create video Reader object
Vptr = VideoReader('VIDE01.mp4');
%Find number of frames
NFrames = round(Vptr.FrameRate*Vptr.Duration);
%Create Video Writer Object
Wptr = VideoWriter('VIDEO_NOISY.mp4','MPEG-4');
%Open the output video file
open(Wptr);
for i=1:NFrames
%Read from video file
Img = readFrame(Vptr);
%Add noise to the image
Img = imnoise(Img,'salt & pepper');
%write to video file
writeVideo(Wptr,Img);
end
%Close the output video file
close(Wptr);
EXPLANATION:
All the frames in the input video is processed and then written to an output file. Here, noise is added to each frame in the intermediate step and then written to the output video file. However, instead of addition of noise, the image can be enhanced or processed in the intermediate step.
EXAMPLE:
%EXAMPLE - VIDEO PROCESSING
%Set the frame rate
%Adjust the Image intensity
%Crop the Image
%Read 250 Frames
Vptr = VideoReader('VIDE01.mp4');
%Find number of frames
NFrames = round(Vptr.FrameRate*Vptr.Duration);
%Create Video Writer Object
Wptr = VideoWriter('VIDEO_Enhance.mp4','MPEG-4');
Wptr.FrameRate = 10;
%Open the output video file
open(Wptr);
for i=1:230
%Read from video file
Img = readFrame(Vptr);
%Adjust the image intensity
Img = imadjust(Img,[0 0 0; 0.7 0.7 0.5],[]);
%Crop undesired portion
Img = Img(1:end,251:end,:);
%write to video file
writeVideo(Wptr,Img);
end
%Close the output video file
close(Wptr);
EXPLANATION:
In this example, the frame rate is set to 10 and Instead of reading all the frames(319), 230 frames are read starting from the first frame. Each frame is enhanced and a portion of it is cropped as well.
HSV color space can be used for assigning different colors to the foreground and background of the same image conveniently in comparison to the equivalent RGB image. HSV color space consists of 3 components namely the Hue, the Saturation and the Value.
In MATLAB, HSV color space of an image is three dimensional matrix and each matrix represents each of the 3 component (Hue,Saturation,Value). Hue and saturation range between zero and one. While saturation defines colorfulness hue is specific to the color.
%MATLAB CODE:
A = imread('swimmer.jpg');
figure,imshow(A);title('Original Image');
Original Image
HSV = rgb2hsv(A);
H = HSV(:,:,1); %Hue
figure,imshow(H);colorbar;
Hue
H( H > mean2(H) ) = 1;
HSV(:,:,1) = H;
C = hsv2rgb(HSV);
figure,imshow(C);title('Hue Modified');
Hue Modified
EXPLANATION:
The original image is in RGB format and it is converted to HSV color space using the MATLAB command ‘rgb2hsv’. The resultant is a three dimensional matrix with Hue, Saturation and Value components in each one of them. By comparing the original RGB image and the Hue component, we can understand that the blue color as high value comparing to other colors in the original image.
Hue is a color wheel, where the colors start from red, then move on to yellow, green, cyan, blue, magenta and ends up again in red.
In our example,the values above the average in the Hue matrix is made 1.(i.e. red). The background of the image is changed from blue to red.
If the whole image including the swimmer needs to be changed to red then instead of finding the average or masking the image, assign zero or 1 to Hue matrix.
After the modification, use ‘hsv2rgb’ command to return back to RGB color space.
%MATLAB CODE:
HSV = rgb2hsv(A);
S = HSV(:,:,2); %Saturation
figure,imshow(S);colorbar;
Saturation
S(:,:)=0;
HSV(:,:,2) = S;
C = hsv2rgb(HSV);
figure,imshow(C);title('Saturation Modified');
Saturation Modified
EXPLANATION:
In this example, the saturation component is modified. The high values of Saturation illustrates that the regions are bright and colorful while the low values illustrates that they are dull and colorless.When saturation matrix is made zero, the colorfulness is completely lost. The above figure clearly shows the gray shade image that is obtained as a result of modifying the saturation matrix.
In this example, both the Hue and the Saturation matrices are modified simultaneously. The background color is changed from blue to green after changing the Hue matrix. The Saturation matrix is changed partially such that the background is not affected but the color on the swimmer is made gray.
In this example, the background color is made shades of gray while the swimmer still retains the color. The masking is done based on the foreground and background on the saturation matrix and a value of zero is assigned to the background and one is assigned to foreground. From this example, it is evident that if the saturation matrix contains zero then the image in RGB color space will contain shades of gray whereas if the saturation matrix contains one then it will contain fully saturated more colorful image in the RGB color space.
The image(Figure.1) above shows the swimmer and different background colors by modifying the Hue matrix.
Transformation of a gray scale image into pseudo color image helps in better visualization of the image. In this tutorial, different ways to apply pseudo color transformation to a gray scale image will be discussed along with the MATLAB Code.
The main idea behind pseudo color transformation is to perform three independent transformation (RED,GREEN and BLUE) on the grayscaleor intensity image and map the corresponding intensity value in the image to the result obtained.
Steps to be performed:
Functional Block Diagram
Reference: Digitial Image Processing by Gonzalez
MATLAB CODE:
%READ AN INPUT IMAGE
A = imread('cameraman.tif');
%PRE-ALLOCATE A MATRIX
Output = zeros([size(A,1) size(A,2) 3]);
%Define a colormap
map = colormap(jet(256));
%Assign the columns to 1-D RED,GREEN and BLUE
Red = map(:,1);
Green = map(:,2);
Blue = map(:,3);
%MAP THE COLORS BASED ON THE INTENSITY OF THE IMAGE
The above code is to combine two colormaps to obtain checkboard effect on the image. To obtain checkboards in different size change the 'sz' variable with 4,8,16..etc.
