A number of well developed image enhancement techniques, basically categorized into global image processing and adaptive image processing, [1, 2] have been widely used in NDE applications, which help to present high quality images conveying information on voids, cracks and inclusions in samples. These enhancements apply certain algorithms on image data and change the values to generate particular effects. Since the visual effect of an image is determined by two factors, i.e. image data (pixel value) and colormap which assign color display for each intensity covering the whole range, the enhancement of the display of an image can be achieved by working on the colormap for a pseudo-color display without actually affecting the image data. A grey scale display can be treated as a special case of pseudo-color. With the advent of high quality color monitors and color output devices available for the scientific workstations whose colormaps can be easily redefined by users, it often is more efficient to manipulate the colormaps to achieve the desired visual effect. Since a typical image file with 8 bits/pixel data can easily contain 250,000 bytes while a colormap for the display of such image requires only 768 bytes for 24 bits/color (corresponding to 16.7 million different shades of colors), the gain in speed obtained by adjusting the colormap rather than the data can be very dramatic.