In my previous postings on this topic, I've discussed the basic image display models in MATLAB - truecolor and indexed. The Image Processing Toolbox has conventions for two additional image display models: grayscale and binary.
theta = linspace(0, 2*pi, 256); I = repmat((-cos(2*theta) + 1)/2, [256 1]); h = imshow(I); % Save the handle for use below.
As far as MATLAB itself is concerned, this is a scaled indexed image being displayed in a figure with a grayscale colormap installed. Here are the key properties that have been set to control the image display:
ans = scaled
The toolbox convention is that, for floating-point images, 0 is displayed as black and 1 is displayed as white.
ans = 0 1
map = get(gcf, 'Colormap'); map(1:5, :) % Display the first few colormap colors
ans = 0 0 0 0.0039 0.0039 0.0039 0.0078 0.0078 0.0078 0.0118 0.0118 0.0118 0.0157 0.0157 0.0157
imshow (and imtool) handle all these details for you.
imshow and imtool allow you to override the conventional display range and specify your own black and white values. You do this by providing a second input argument, a two-element vector containing the black and white values. In the call to imshow below, 0.4 (and any lower value) gets displayed as black. The value 0.6 (and any higher value) gets displayed as white.
imshow(I, [0.4 0.6])
The other Image Processing Toolbox image display model is the binary image. If you supply a single input argument that is logical, then imtool and imshow (as well as many other toolbox functions) interpret that input as a binary image.
bw = imread('text.png'); islogical(bw)
ans = 1
h = imshow(bw);
The Image Processing Toolbox Users Guide has a section called "Image Types in the Toolbox." This section describes the image types binary, indexed, grayscale, and truecolor, and it explains important dynamic range conventions as well. This is essential information for you to know in order to use the toolbox effectively.
Get the MATLAB code
Published with MATLAB® 7.2