Download e-book for iPad: An Introduction to Digital Image Processing with MATLAB by Alasdair McAndrew

By Alasdair McAndrew

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18. 29: Further reducing the resolution of an image 34 CHAPTER 1. 30: Even more reducing the resolution of an image Exercises 1. Watch the TV news, and see if you can observe any examples of image processing. 2. If your TV set allows it, turn down the colour as far as you can to produce a monochromatic display. How does this affect your viewing? Is there anything which is hard to recognize without colour? 3. Look through a collection of old photographs. How can they be enhanced, or restored? 4.

This is far more spread out than the original histogram, and so the resulting image should exhibit greater contrast. 3. HISTOGRAMS 51 applies histogram equalization to the pout image, and produces the resulting histogram. 19. Notice the far greater spread of the histogram. 8 after equalization to the greater increase of contrast in the image. We give one more example, that of a very dark image. We can obtain a dark image by taking an image and using imdivide. tif’); >> e=imdivide(en,4); Since the matrix e contains only low values it will appear very dark when displayed.

17. associated with a table of the numbers ✂✁ of grey values: Grey level ✄ ✆✁ ✏ ✥ ✜ ✥ ✏ ✒ ✥ ✛ ✥ ✥ ✜ ✪ ✥ ✥ ✢ ☎ ✥ ✭ ✥ ✭ ✥ ✏ ✏✏ ✥ ✥ ✒ ✛ ✜ ✏ ✏ ✢✏ ✥ ✛ ✏ ✥ ✏ ✥ ✏ ✥ ✛ ✜ 50 CHAPTER 2. ) We would expect this image to be uniformly bright, with a few dark dots on it. 18. This is far more spread out than the original histogram, and so the resulting image should exhibit greater contrast. 3. HISTOGRAMS 51 applies histogram equalization to the pout image, and produces the resulting histogram. 19. Notice the far greater spread of the histogram.

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An Introduction to Digital Image Processing with MATLAB (draft) by Alasdair McAndrew


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