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The Image Object and Its Properties

Image CData

Note

The image and imagesc commands create image objects. Image objects are children of axes objects, as are line, patch, surface, and text objects. Like all graphics objects, the image object has a number of properties you can set to fine-tune its appearance on the screen. The most important properties of the image object with respect to appearance are CData, CDataMapping, XData, and YData. These properties are discussed in this and the following sections. For detailed information about these and all the properties of the image object, see image.

The CData property of an image object contains the data array. In the following commands, h is the handle of the image object created by image, and the matrices X and Y are the same:

h = image(X); colormap(map)
Y = get(h,'CData');

The dimensionality of the CData array controls whether the image displays using colormap colors or as an RGB image. If the CData array is two-dimensional, the image is either an indexed image or an intensity image; in either case, the image is displayed using colormap colors. If, on the other hand, the CData array is m-by-n-by-3, it displays as a truecolor image, ignoring the colormap colors.

Image CDataMapping

The CDataMapping property controls whether an image is indexed or intensity. To display an indexed image set the CDataMapping property to 'direct', so that the values of the CData array are used directly as indices into the figure's colormap. When the image command is used with a single input argument, it sets the value of CDataMapping to 'direct':

h = image(X); colormap(map)
get(h,'CDataMapping')
ans =

direct

Intensity images are displayed by setting the CDataMapping property to 'scaled'. In this case, the CData values are linearly scaled to form colormap indices. The axes CLim property controls the scale factors. The imagesc function creates an image object whose CDataMapping property is set to 'scaled', and it adjusts the CLim property of the parent axes. For example:

h = imagesc(I,[0 1]); colormap(map)
get(h,'CDataMapping')
ans =

scaled

get(gca,'CLim')
ans =

[0 1]

XData and YData

The XData and YData properties control the coordinate system of the image. For an m-by-n image, the default XData is [1 n] and the default YData is [1 m]. These settings imply the following:

  • The left column of the image has an x-coordinate of 1.

  • The right column of the image has an x-coordinate of n.

  • The top row of the image has a y-coordinate of 1.

  • The bottom row of the image has a y-coordinate of m.

Coordinate System for Images

Use Default Coordinate System

Display an image using the default coordinate system. Use colors from the colorcube map.

C = [1 2 3 4; 5 6 7 8; 9 10 11 12];
im = image(C);
colormap(colorcube)

Specify Coordinate System

Display an image and specify the coordinate system. Use colors from the colorcube map.

C = [1 2 3 4; 5 6 7 8; 9 10 11 12];
x = [-1 2];
y = [2 4];
figure
image(x,y,C) 
colormap(colorcube)

Add Text to Image Data

This example shows how to use array indexing to rasterize text into an existing image.

Draw the text in an axes using the text function. Then, capture the text from the screen using getframe and close the figure.

fig = figure;
t = text(.05,.1,'Mandrill Face','FontSize',20,'FontWeight','bold');
F = getframe(gca,[10 10 200 200]);
close(fig)

Select any plane of the resulting RGB image returned by getframe. Find the pixels that are black (black is 0) and convert their subscripts to indexes using sub2ind. Use these subscripts to "paint" the text into the image contained in the mandrill MAT-file. Use the size of that image, plus the row and column locations of the text to determine the locations in the new image. Index into new image, replacing pixels.

c = F.cdata(:,:,1);
[i,j] = find(c==0);
load mandrill
ind = sub2ind(size(X),i,j);
X(ind) = uint8(255);

Display the new image using the bone colormap.

imagesc(X)
colormap bone

Additional Techniques for Fast Image Updating

To increase the rate at which the CData property of an image object updates, optimize CData and set some related figure and axes properties:

  • Use the smallest data type possible. Using a uint8 data type for your image will be faster than using a double data type.

    Part of the process of setting the image's CData property includes copying the matrix for the image's use. The overall size of the matrix is dependent on the size of its individual elements. Using smaller individual elements (i.e., a smaller data type) decreases matrix size, and reduces the amount of time needed to copy the matrix.

  • Use the smallest acceptable matrix.

    If the speed at which the image is displayed is your highest priority, you may need to compromise on the size and quality of the image. Again, decreasing the size reduces the time needed to copy the matrix.

  • Set the limit mode properties (XLimMode and YLimMode) of your axes to manual.

    If they are set to auto, then every time an object (such as an image, line, patch, etc.) changes some aspect of its data, the axes must recalculate its related properties. For example, if you specify

    image(firstimage);
    set(gca, 'xlimmode','manual',...
    'ylimmode','manual',...
    'zlimmode','manual',...
    'climmode','manual',...
    'alimmode','manual');
    

    the axes do not recalculate any of the limit values before redrawing the image.

  • Consider using a movie object if the main point of your task is to simply display a series of images onscreen.

    The MATLAB® movie object utilizes underlying system graphics resources directly, instead of executing MATLAB object code. This is faster than repeatedly setting an image's CData property, as described earlier.