In spite of the availability of advanced imaging devices with high sensitivity, high resolution, and built-in image-data processing procedures, images are often acquired with quality that is unsatisfactory or inadequate for certain purposes. When considering methods to modify such images with the aim of enhancing their quality, it is important to recognize and understand the several notions and factors that affect and determine the quality of an image; see Sections 2.2 and 2.3 as well as Rangayyan . If further analysis of the processed image is to be performed by a human observer, the subjective and qualitative nature of such analysis needs to be taken into consideration. On the other hand, if subsequent analysis of the image is relegated to yet another computational procedure, the objective or quantitative requirements of the procedure should be taken into account in the design of the enhancement procedure. Thus, the nature and extent of enhancement to be effected on an image depend upon further use of the processed image.
In most cases, the enhancement sought in an image would be aimed to achieve one or more of the following desired characteristics:
• uniform or balanced brightness across the image, which may require dark areas to be made lighter and areas of excessive brightness to be made less bright;
• good contrast and visibility of detail;
• sharp and well-defined edges and borders of objects or regions in the image;
• clean and clear representation of the original objects or scene with no noise or blemishes;
• faithful reproduction of hues or shades of color, with particular attention to skin tone and hue in images of humans; and
• good color balance to result in a pleasant appearance.
Several digital image-processing techniques have been proposed to address the requirements stated above in the case of grayscale images [1, 6]. However, the extension of techniques designed for grayscale or monochromatic images to process color or vector images is neither straightforward nor always appropriate; the methods described in Chapter 3 to remove noise in color images illustrate some related concepts and methods.