Name
equ_histo_imageequ_histo_imageEquHistoImageequ_histo_imageEquHistoImageEquHistoImage — Histogram linearisation of images
The operator equ_histo_imageequ_histo_imageEquHistoImageequ_histo_imageEquHistoImageEquHistoImage enhances the contrast. The
starting point is the histogram of the input images. The following
simple gray value transformation f(g) is carried out for byte
images:
h(x) describes the relative frequency of the occurrence of the
gray value x. For uint2 images, the only difference is that the
value 255 is replaced with a different maximum value. The maximum
value is computed from the number of significant bits stored with
the input image, provided that this value is set. If not, the value
of the system parameter 'int2_bits'"int2_bits""int2_bits""int2_bits""int2_bits""int2_bits" is used (see
set_systemset_systemSetSystemset_systemSetSystemSetSystem), if this value is set (i.e., different from -1).
If none of the two values is set, the number of significant bits is
set to 16.
This transformation linearises the cumulative histogram. Maxima in
the original histogram are “spreaded” and thus the contrast in
image regions with these frequently occuring gray values is
increased. Supposedly homogenous regions receive more easily visible
structures. On the other hand, of course, the noise in the image
increases correspondlingly. Minima in the original histogram are
dually “compressed”. The transformed histogram contains gaps, but
the remaining gray values used occur approximately at the same
frequency (“histogram equalization”).
The operator equ_histo_imageequ_histo_imageEquHistoImageequ_histo_imageEquHistoImageEquHistoImage primarily serves for
optical processing of images for a human viewer. For example, the
(local) contrast spreading can lead to a detection of fictitious edges.
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Automatically parallelized on tuple level.
- Automatically parallelized on channel level.
Image with linearized gray values.
disp_imagedisp_imageDispImagedisp_imageDispImageDispImage
scale_imagescale_imageScaleImagescale_imageScaleImageScaleImage,
scale_image_maxscale_image_maxScaleImageMaxscale_image_maxScaleImageMaxScaleImageMax,
illuminateilluminateIlluminateilluminateIlluminateIlluminate
scale_imagescale_imageScaleImagescale_imageScaleImageScaleImage
R.C. Gonzales, P. Wintz: “Digital Image Processing”; Second edition;
Addison Wesley; 1987.
Foundation