What Will We Learn?
- What does it mean to “enhance” an image?
- How can image enhancement be achieved using gray-level transformations?
- What are the most commonly used gray-level transformations and how can they be implemented using MATLAB?
This chapter—and also Chapters 9 and 10—will discuss the topic of image enhancement in the spatial domain. As discussed in Chapter 1, image enhancement techniques usually have one of these two goals:
1. To improve the subjective quality of an image for human viewing.
2. To modify the image in such a way as to make it more suitable for further analysis and automatic extraction of its contents.
In the first case, the ultimate goal is an improved version of the original image, whose interpretation will be left to a human expert—for example, an enhanced X-ray image that will be used by a medical doctor to evaluate the possibility of a fractured bone. In the second scenario, the goal is to serve as an intermediate step toward an automated solution that will be able to derive the semantic contents of the image—for example, by improving the contrast between characters and background on a page of text before it is examined by an OCR algorithm. Sometimes these goals can be at odds with each other. For example, sharpening an image to allow inspection of additional fine-grained details is usually desired for human viewing, whereas blurring an image to reduce the amount of irrelevant information is ...