Page 201 - MATLAB Recipes for Earth Sciences

196 8 Image Processing

map is an m-by-3 array of real numbers between 0.0 and 1.0. Each row is a

RGB vector that defines one color by means of intensities of red, green and
blue. Numerous global colormaps for the interpretation of 8-bit color im-
ages exist that allow the cross-platform exchange of raster images, whereas
local colormaps are often embedded in a graphics fi le.
The disadvantage of 8-bit color images is that the 256 discrete colorsteps
are not enough to simulate smooth transitions for the human eye. Therefore,
in many applications a 24-bit system is used with 8 bits of data for each
RGB channel giving a total of 256 =16,777,216 colors. Such a 24-bit image
3
is therefore stored in three 2D arrays or one 3D array of intensity values
between 0 and 255.
195 189 203 217 217 221
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190 192 193 191 184 190
186 179 178 182 180 169

209 203 217 232 232 236
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174 168 182 199 199 203
198 189 167 172 184 185
188 199 193 178 168 172
186 186 185 183 174 185
177 177 178 176 171 177
179 171 168 170 170 163

Compared to 1-bit and 8-bit representation of raster data, the 24-bit stor-
age certainly requires a lot more computer memory. In the case of very
large data sets such as satellite images and digital elevation models the user
should therefore carefully think about the suitable way to store the data.
The default data type in MATLAB is the 64-bit array which allows to store

the sign of a number (first bit), the exponent (bits 2 to 12) and roughly 16
significant decimals digits in the range of roughly 10 -308 and 10 +308 (bits 13

to 64). However, MATLAB also works with other data types such as 1-bit,
8-bit and 24-bit raster data to save memory.
The amount of memory required for storing an image depends on the data
type and the raster dimension. The dimension of an image can be described
by the numbers of pixels, which is the number of rows multiplied by the
number of columns of the 2D array. Assume an image of 729x713 pixels, as