One of the main applications of wavelets is in the area of image processing. Wavelets can be used to denoise images, perform image compression, search for edges in images, and enhance image features. Indeed, since two chapters of this book are dedicated to denoising and compression, and examples involving images are featured throughout the text, we include this chapter on the basics of digital images.

It is quite tempting to dedicate many pages to the various aspects of image processing. In this chapter we discuss the basic material necessary to successfully navigate through the remainder of the text. If you are interested in more thorough treatments on the numerous topics that comprise digital image processing, I might suggest you start by consulting Russ [64], Gonzalez and Woods [39], Gonzalez, Woods, and Eddins [40], or Wayner [84].

This chapter begins with a section that introduces digital grayscale images. We learn how digital images can be interpreted by computer software and how matrices are important tools in basic image-processing applications. We also discuss intensity transformations. These transformations are commonly used to improve the image display. Section 3.2 deals with digital color images as well as some popular color spaces that are useful for image processing. In the third section of the chapter we introduce some qualitative and quantitative measures that are useful when assessing the effectiveness of image-processing ...

Get Discrete Wavelet Transformations: An Elementary Approach with Applications now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.