[Digital Image Processing (I)] overview of digital image processing and related fields

Digital Image)

An image can be defined as a two-dimensional function f (x, y). Here, X and Y are spatial coordinates, and in any coordinate (x, y) the amplitude F is called the brightness or gray scale of the image at the coordinate position. When the amplitude of X, Y, and F are finite discrete values, they are called digital images. Note that a digital image consists of a limited number of elements, each of which has a special position and value. These elements are called portrait elements, image elements, and pixels. pixels are the most widely used term for defining digital image elements. -- Digital Image pricessing using Matlab (rafacel C. gonzarez)
A digital image is a large two-dimensional array obtained by sampling and digitization using digital cameras, scanners, and other devices. The elements of this array are called pixels. The value of this array is an integer and is called a gray value. -- Baidu encyclopedia

Image processing, image analysis, machine vision, computer vision

Is a closely related discipline. If you open a textbook with the above names, you will find that they overlap a considerable part of the technology and application fields. The basic theories of these disciplines are roughly the same. However, due to different fields of interest, different research institutions, academic journals, conferences, and companies often classify themselves as one of the most important fields, therefore, various characteristics used to distinguish these disciplines are proposed.

Digital Image Processing)

Digital image processing is a process and technology that uses computers to remove noise, enhance, restore, split, and extract features from digital images. (Mainly studying two-dimensional images)

Image Analysis)

Image analysis uses mathematical models and image processing techniques to analyze underlying features and upper-layer structures, so as to extract information with certain intelligence. (Mainly studying two-dimensional images)

Machine Vision)

Machine Vision uses machines instead of human eyes for measurement and judgment. A machine vision system refers to a machine vision product (I .e., an image uptake device, which is divided into CMOS and CCD) to convert the uptake target into an image signal and transmit it to a dedicated image processing system, digital signals are converted based on Pixel Distribution, brightness, color, and other information. Image systems perform various operations on these signals to extract target features, then, efficient machine control or various real-time operations are achieved based on the identified results. (Mainly used in the industrial field)

Computer Vision)

Computer Vision is a simulation of Biological vision using computers and related devices. Its main task is to process the collected images or videos to obtain three-dimensional information of the corresponding scene, as humans and many other types of creatures do on a daily basis. (Mainly studying three-dimensional information)

Let's take a look at the following three types of computer processing:

• Low-level processing: includes original operations on the image, such as noise reduction, contrast enhancement, and image sharpening. Specifically, both input and output are images;
• Intermediate processing: includes image classification and Feature Extraction (such as edge, contour, and area ). The feature is that the input is usually an image, and the output is a feature extracted from these images;
• Advanced processing: provides an overall understanding of the image (such as face recognition) and implements cognitive functions normally related to human vision;

Based on the previous understanding, there is no clearly defined boundary between the processes just discussed. According to my personal understanding, I prefer to understand digital image processing

1. Both input and output are image processing;
2. Extract features from images.

MATLABIt is a major tool in the field of image processing. Next, we will learn about image processing and how to use MATLAB to implement some image processing algorithms.