Python Programming for Biology: Bioinformatics and Beyond

Figure 18.2 (Plate 6).  An image, its component pixels and their RGB colour-space

values. A section of the book cover picture is shown magnified at different levels to reveal

the array of square pixels that the digital image is composed of. For the highest

magnification, example pixels with different colours are selected and the component red,

green and blue (RBG) values that constitute each colour are shown as histograms.

Once we know how image data is stored we will need to be able to manipulate it. In this

chapter  we  will  generally  be  working  with  greyscale  or  the  RGB  colour  model  for

simplicity,  but  we  will  illustrate  how  to  convert  to  and  from  the  other  representations.

When performing more mathematical operations with numeric Python we will think of the

pixels in an image as being elements of a matrix (a 2D array) and often we can think of the

different  red,  green  and  blue  components  as  separate  layers  (also  called  channels)  each

with a separate matrix, which are then arranged depth-wise to make the full pixmap.