  When the sampling data of ghost imaging is recorded with less bits, i.e.,
experiencing quantization, decline of image quality is observed. The less bits
used, the worse image one gets. Dithering, which adds suitable random noise to
the raw data before quantization, is proved to be capable of compensating image
quality decline effectively, even for the extreme binary sampling case. A brief
explanation and parameter optimization of dithering are given.
