
Introduction to Advanced Image Processing Operations
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We will extend our coverage of image processing. We will some previously discussed techniques in more depth, and introduce some additional ones.
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We will extend our coverage of image processing. We will some previously discussed techniques in more depth, and introduce some additional ones.
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Let’s learn how to import a color image into MATLAB and see how the data is organized as a matrix with three dimensions.
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Let’s recap some of the most important topics we’ve covered about treating an image as a matrix within MATLAB which we can display or index into.
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Image warping allows us to shrink (or expand) an image by any scale factor, as well as to translate and rotate it. Let’s look at how image warping works.
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Image warping allows us to shrink (or expand) an image by any scale factor, as well as to translate and rotate it. Let’s look at how image warping works.
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Most computers today have a built-in camera. Let’s look at how we can grab images directly from such a camera and put them in the MATLAB workspace.
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An important class of operations are monadic, which map an input image to an output image of the same size by applying the same function to every pixel.
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Since an image in MATLAB is just a matrix of numbers, we could write code to fill in the elements of the matrix. Let’s look at some simple examples such as squares, circles and lines and more complex images formed by pasting these shapes together.
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There are a lot of pixels in a typical image which makes them take up a lot of memory. Images can be compressed to take up less storage. Compression can be lossless or lossy, where we tradeoff size for quality.
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Digital images are everywhere: in your phone, on your hard drive, on the internet. We can access still pictures, movies and streams from live cameras all around the world. Let’s talk about digital images and how we can get them into the MATLAB environment where we can work on them.