The value 0 corresponds to black and the value 1 corresponds to white. This assigns a floating number ("a number with decimals") between 0 and 1 to each pixel. There are two ways to represent the number that represents the brightness of the pixel: The double class (or data type).
It represents an image as a matrix where every element has a value corresponding to how bright/dark the pixel at the corresponding position should be colored. This is the equivalent to a "gray scale image" and this is the image we will mostly work with in this course. This section explains four common formats. However, in order to start working with an image, for example perform a wavelet transform on the image, we must convert it into a different format. If an image is stored as a JPEG-image on your disc we first read it into Matlab. For example, an image named myimage.jpg is stored in the JPEG format and we will see later on that we can load an image of this format into Matlab. If you have stored an image you can usually see from the suffix what format it is stored in. Most images you find on the Internet are JPEG-images which is the name for one of the most widely used compression standards for images. The following image formats are supported by Matlab:
There are also a few "computer scientific" tricks (for example entropy coding) to reduce the amount of data required to store an image. You will later on see how Fourier analysis and Wavelet analysis can help us to compress an image significantly. This means that the data for the image must contain information about 524288 pixels, which requires a lot of memory! Hence, compressing images is essential for efficient image processing. Let us say that we have an image on the format 512-by-1024 pixels. In the general case we say that an image is of size m-by- n if it is composed of m pixels in the vertical direction and n pixels in the horizontal direction. Later on in the course you will see that it is convenient to let the dimensions of the image to be a power of 2. A typical size of an image is 512-by-512 pixels.
We will see in detail later on how this is done in practice.
#How to convert file format in matlab how to#
A digital image is an instruction of how to color each pixel. Once you can get these examples to work, experiment on your own using your favorite image!Ī digital image is composed of pixels which can be thought of as small dots on the screen. The only way to understand how the presented commands work, is to carefully work through the examples given at the end of the worksheet. The first sections of this worksheet are quite heavy.
#How to convert file format in matlab manual#
There is an extensive (and quite good) on-line manual for the Image processing tool box that you can access via Matlab's help browser. This gives you a list of what tool boxes that are installed on your system.įor further reference on image handling in Matlab you are recommended to use Matlab's help browser. To find out if it is installed, type ver at the Matlab prompt. Most of these commands require you to have the Image processing tool box installed with Matlab. This worksheet presents some of the commands designed for these operations. When working with images in Matlab, there are many things to keep in mind such as loading an image, using the right format, saving the data as different data types, how to display an image, conversion between different image formats, etc. This worksheet is an introduction on how to handle images in Matlab. Introduction to image processing in Matlab 1 Introduction to image processing in Matlab 1 by Kristian Sandberg, Department of Applied Mathematics, University of Colorado at Boulder
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