ABSTRACT
Digital image processing is a field that continues to grow, with new applications being developed at an ever-increasing pace. Digital image processing can be defined as the acquisition and processing of visual information by computer. This introductory chapter provides an overview of digital image processing with a focus on image analysis and computer vision applications. The image analysis process requires the use of tools such as image segmentation, image transforms, feature extraction and pattern classification. Image segmentation is often one of the first steps in finding higher-level objects from the raw image data. Feature extraction and analysis is the process of acquiring higher-level image information, such as shape or color information, and it may require the use of image transforms to find spatial frequency information. Pattern classification is the act of taking this higher-level information and identifying objects within the image. Various methods of image acquisition are discussed including visible light imaging and how the non-visible parts of the electromagnetic spectrum are used to generate images. A brief look at lenses and lighting and imaging sensors is included. The two key components of image formation are discussed. Additionally, acoustic, electron and laser imaging methods and their applications are discussed. Image representation and display is considered, including binary, color and multispectral images. Useful color transforms are provided and discussed. An overview of a number of commonly used file formats for image storage is included. Along with the text are 35 illustrative figures and 68 associated color images. Problems are included at the chapter end.
