Definition of Digital Image Processing

The Research of Digital Image Processing Methods comes from two main application fields: (1) Improving Image Information for convenience of analysis; (2) various analysis and research performed to give machines the ability to analyze and understand images similar to humans;

An image can be defined as a two-dimensional function f (x, y). Here, X and Y are spatial coordinates. The amplitude F on any spatial coordinate (X, Y) is called the intensity or gray scale of the image at this point. When x, y, and F are finite and discrete values, they are called images. Simply put, a digital image is composed of limited elements, each of which has a specific position and amplitude. These elements are called elements or pixels of an image.

Image processing has a wide range of research areas. Here, I am afraid to divide the application of image processing into three parts:

(1) grayscale, color enhancement, noise removal, brightness adjustment, Local restoration, and blur; the most typical application of this category is Photoshop.

(2) image segmentation and contour extraction. For example, in remote sensing geographic information systems, aerial images are often analyzed to determine environmental pollution in a region.

(3) image-based content analysis, understanding, and recognition, such as License Plate Recognition, iris recognition, and face recognition.

It should be noted that (1) it should be said that it is the simplest and easiest in the field of image processing. It can be said that it is purely "image processing ". (3) It is the most complex and difficult field. It belongs to the scope of computer vision. The ultimate goal is to enable machines (generally computers) to have human visual functions, ability to intelligently analyze and understand what you see. It not only involves simple image processing, but also integrates Pattern Recognition and machine learning knowledge.