In gray images which contain abundant information, if the differences between adjacent pixels’ intensity are small, the
required information can not be extracted by humans, since humans are more sensitive to color images than gray images.
If gray images are transformed to pseudo-color images, the details of images will be more explicit, and the target will be
recognized more easily. There are two methods (in frequency field and in spatial field) to realize pseudo-color
enhancement of gray images. The first method is mainly the filtering in frequency field, and the second is the equal
density pseudo-color coding methods which mainly include density segmentation coding, function transformation and
complementary pseudo-color coding. Moreover, there are many other methods to realize pseudo-color enhancement,
such as pixel’s self-transformation based on RGB tri-primary, pseudo-color coding from phase-modulated image based
on RGB color model, pseudo-color coding of high gray-resolution image, et al. However, above methods are tailored to a
particular situation and transformations are based on RGB color space. In order to improve the visual effect, the method
based on RGB color space and pixels’ self-transformation is improved in this paper, which is based on HIS color space.
Compared with other methods, some gray images with ordinary formats can be processed, and many gray images can be
transformed to pseudo-color images with 24 bits. The experiment shows that the processed image has abundant levels,
which is consistent with human’s perception.