Python Programming for Biology: Bioinformatics and Beyond

Figure 18.4.  Example results from common image-processing operations. An

original microscope image of mammalian cells is shown alongside five adjusted versions

created with image-processing routines presented here. The gamma adjustment used a

factor of 4.0. The blurred, sharpened and edge-detected images were generated by matrix

convolution. The intensity clipping set the lightest pixels to mid-grey and then normalised

the intensities to the full black-white range.

If  we  want  to  perform  a  different  kind  of  adjustment  we  need  to  make  a  different

processing object. The next example is for image sharpness (changing the local contrast at

the edges within an image), where we can make things sharper with a value greater than

one, or more blurred with a value less than one:

processObj = ImageEnhance.Sharpness(img)

img2Sharp = processObj.enhance(4.0)

img2Sharp.show()

imgBlur = processObj.enhance(0.5)

imgBlur.show()

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Likewise,  we  can  adjust  brightness  and  overall  colourfulness,  noting  that  in  the  next

examples  we  use  the  method  .enhance()  straight  away,  and  don’t  make  an  explicit

processing  object;  the  object  is  still  made  after  .Brightness(img),  but  it  is  not  given  a

named variable.

imgBrighter = ImageEnhance.Brightness(img).enhance(0.5)

imgDull = ImageEnhance.Color(img).enhance(0.1)