Image Processing Toolbox

Converting Image Types

For certain operations, it is helpful to convert an image to a different image type. For example, if you want to filter a color image that is stored as an indexed image, you should first convert it to RGB format. When you apply the filter to the RGB image, MATLAB filters the intensity values in the image, as is appropriate. If you attempt to filter the indexed image, MATLAB simply applies the filter to the indices in the indexed image matrix, and the results may not be meaningful.

Note    When you convert an image from one format to another, the resulting image may look different from the original. For example, if you convert a color indexed image to an intensity image, the resulting image is grayscale, not color. For more information about how the image conversion functions listed below, see their reference pages.

The following table lists all the image conversion functions in the Image Processing Toolbox.

Function	Description
dither	Create a binary image from a grayscale intensity image by dithering; create an indexed image from an RGB image by dithering
gray2ind	Create an indexed image from a grayscale intensity image
grayslice	Create an indexed image from a grayscale intensity image by thresholding
im2bw	Create a binary image from an intensity image, indexed image, or RGB image, based on a luminance threshold
ind2gray	Create a grayscale intensity image from an indexed image
ind2rgb	Create an RGB image from an indexed image
mat2gray	Create a grayscale intensity image from data in a matrix, by scaling the data
rgb2gray	Create a grayscale intensity image from an RGB image
rgb2ind	Create an indexed image from an RGB image

You can also perform certain conversions just using MATLAB syntax. For example, you can convert an intensity image to RGB format by concatenating three copies of the original matrix along the third dimension.

• RGB = cat(3,I,I,I);
  

The resulting RGB image has identical matrices for the red, green, and blue planes, so the image displays as shades of gray.

In addition to these standard conversion tools, there are some functions that return a different image type as part of the operation they perform. For example, the region-of-interest routines each return a binary image that you can use to mask an indexed or intensity image for filtering or for other operations.

Color Space Conversions

The Image Processing Toolbox represents colors as RGB values, either directly (in an RGB image) or indirectly (in an indexed image). However, there are other methods for representing colors. For example, a color can be represented by its hue, saturation, and value components (HSV). Different methods for representing colors are called color spaces.

The toolbox provides a set of routines for converting between RGB and other color spaces. The image processing functions themselves assume all color data is RGB, but you can process an image that uses a different color space by first converting it to RGB, and then converting the processed image back to the original color space. For more information about color space conversion routines, see Color.

Summary of Image Types and Numeric Classes

Working with Image Data