By Alasdair McAndrew

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**Extra resources for An Introduction to Digital Image Processing with MATLAB (draft) **

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26. 26(b). A very disappointing image! But this is to be expected; in a matrix of type uint8, white is 255, 0 is black, and 1 is a very dark grey–indistinguishable from black. 26. 30 CHAPTER 1. 17 Bit planes Greyscale images can be transformed into a sequence of binary images by breaking them up into their bit-planes. If we consider the grey value of each pixel of an 8-bit image as an 8-bit binary word, then the 0th bit plane consists of the last bit of each grey value. Since this bit has the least effect in terms of the magnitude of the value, it is called the least significant bit, and the plane consisting of those bits the least significant bit plane.

18 Spatial Resolution Spatial resolution is the density of pixels over the image: the greater the spatial resolution, the more pixels are used to display the image. 18. 27: The bit planes of an 8-bit greyscale image 32 CHAPTER 1. INTRODUCTION imresize function. Suppose we have an Then the command ✜ ✪ ✜ ✪ ✣ 8-bit greyscale image saved to the matrix x. imresize(x,1/2); will halve the size of the image. It does this by taking out every other row and every other column, thus leaving only those matrix elements whose row and column indices are even: ☛ ☛ ✔ ☛ ☛ ☎ ☛ ✌ ☛ ✄ ☛ ✌ ✗☎ ☛ ☛ ☛ ✂☎ ☛ ✕✄ ☛ ..

We have seen examples of this above with scaling. Corresponding to the functions double and im2double are the functions uint8 and im2uint8. If we take our image cd of type double, properly scaled so that all elements are between 0 and 1, we can convert it back to an image of type uint8 in two ways: >> c2=uint8(255*cd); >> c3=im2uint8(cd); Use of im2uint8 is to be preferred; it takes other data types as input, and always returns a correct result. Binary images Recall that a binary image will have only two values: 0 and 1.