Halftoning is a process of transforming a gray scale image to a halftone (only black
and white). It creates the illusion of gray-scale by varying the average dot density in
local regions of images. Halftoning takes the advantage of the fact that eyes integrate
intensity of small image regions as in Fig.1.6. However, spatial resolution must be
sacrificed (output image will be larger than the original), which refers to image
itself based on direct manipulation pixels, for gray-scale resolution unless the output
device can be over-sampled as most ink-jet printers.
A gray scale image is transformed to a halftoned image in the domain of printing
media by using physical filters, lights, and film. The illusion of gray scale is obtained
by varying sizes and shapes of ink dots. However, digital halftoning cannot be done
this way since digital images consist of identically shaped pixels, which is either
black or white. The main problem is to decide whether this pixel should be white or
black.
Now, consider the solutions of digital halftoning consisting of bi-level thresholding
and font/pattern replacement.
Bi-level Thresholding: Bi-level thresholding requantizes an image using one bit
color. If the gray-scale of a pixel is less than some threshold value, then set the
output to be black otherwise set the output to be white. Fig.1.8 shows the process of
the bi-level thresholding method, when the bi-level thresholding process is applied
for gray scale images with the range from zero to 255. Fig.1.8 shows the diagram of
bi-level thresholding.
A key parameter of bi-level thresholding is a threshold value. There are several
ways in deriving a threshold. The threshold value may be the center of available gray
scale range. For example, if the gray scale range is from zero to 255, a threshold
value can be set to 128. Pixel values that are higher than 128 will be set to 255,
whereas pixel values that are lower than or equal to 128 will be set to zero. The
threshold can be also set as an average of all pixels in an image or the average of the
maximum and minimum value of gray scale pixels in an image. For example, if the
maximum and minimum values of gray scale pixels are 200 and 100, respectively,