1. Digital image
In the objective world, an image presented in a natural form is usually called a physical image , also called a continuous image, and the value of the image signal changes continuously. Because computers can only recognize discrete numbers, physical images need to be processed and converted into digital forms, that is, digital images before they can be used. A digital image is a representation of a two-dimensional image with limited digital value pixels. It is represented by an array or matrix, and its light position and intensity are all discrete. Digital images are images obtained by digitizing analog images , with pixels as the basic elements, and images that can be stored and processed by digital computers or digital circuits. In
normal life, digital cameras are a kind of electronic sensors that convert optical images into electronic data . camera. The difference between a mobile phone camera and a digital camera lies in the difference in photosensitive components and other aspects. There are two ways to store
digital images : bitmap storage and vector storage. A bitmap image is also called a bitmap image or a bitmap image. It is an identifiable image composed of a series of pixels . Vector graphics directly describe each point of the image data. Common digital image storage formats: PNG, GIF, JPEG, BMP, etc., are all digital image storage formats.
2. Classification of digital images
The pixel of each image usually corresponds to a specific'location' in the two-dimensional space, and there are one or more sample values related to that point to form a numerical value. According to the number and characteristics of these samples, different digital images can be divided into:
- Binary image
Binary image (Binary Image): luminance value of each pixel in the image (Intensity) images can only be taken from 0 to 1. Gray scale image (Gray Scale Image), also known as gray-scale image: each pixel in the image may be represented by 0 (black) to the brightness value of 255 (white). 0-255 indicates different gray levels.
- Color image
Color Image: Each color image is a combination of three grayscale images of different colors, one is red, one is green, and the other is blue. (RGB)
- False color image
False-color multi-spectral thematic Stereo Image: A stereo image is a pair of images taken from different angles of an object. Normally, we can use the stereo image to calculate the depth information of the image.
- Three-dimensional image
Three-dimensional image (3D Image): A three-dimensional image is composed of a stack of two-dimensional images. Each image shows a cross section of the object.
3. Image basics
We know that the image on the monitor is made up of many dots. These dots are called pixels, which means "the elements that make up the image." As a size of an image, a pixel only exists in a computer. A pixel is a virtual unit. There is no pixel unit in real life.
Screen resolution: the number of pixels on the screen. Display resolution: the display mode resolution provided by the computer display controller. The text display mode is the product of the total number of characters that can be displayed in the horizontal and vertical directions; the graphic display mode is the product of the total number of pixels that can be displayed in the horizontal and vertical directions. Graphics card resolution: The number of pixels that the graphics card outputs to the monitor and can be drawn on the monitor. The highest resolution provided by the computer depends on the lower of the graphics card and monitor
Mainly understand the pixel and resolution.
- Image concept
Image is a kind of similarity to objectively existing objects, vivid pictures or descriptions.
- Image category
The image can be divided into different standards according to different standards, the following is divided into analog image and digital image
The simulated image can be described by a continuous function.
Digital image can be described by matrix or array. Among them, the attributes of the pixel or pixel: indicate the spatial position and grayscale
- Digital image processing
Image digitization: How to obtain a digital image that meets the requirements from an analog image, so that the image is convenient for computer processing and analysis.
Image transformation: focus on learning the Fourier transform algorithm
Image enhancement: enhance the useful information of the image and reduce the interference of noise.
Image restoration and reconstruction: Degradation. Blurred image restoration. And so on technology
- Image digitization
Image digitization is the conversion of a picture into a form that can be processed by a computer. That is, a picture is divided into small areas, and the gray scale of each small area is represented by an integer to form a dot matrix digital image. Including two processes of sampling and quantization. The attribute of the pixel = (position, grayscale/color).
Digital images can be divided into black-and-white images, gray-scale images, and color images according to the difference in the number of gray levels.
Black and white image: each pixel of the image can only be black or white, without intermediate transitions, also known as binary image.
Grayscale image: The information of each pixel is described by a quantized grayscale. There is no color information. 1 byte (8 bits) can represent 256 levels of grayscale (0~255)
Color image: each pixel is an image composed of RGB components. RGB is described by different gray levels, and 3 bytes can represent each channel.
The image digitization process can be divided into sampling and quantization. The larger the sampling interval, the fewer pixels of the resulting image, the larger the sampling interval, the more clear the resulting image pixels, and the larger the amount of data. The larger the quantization level, the richer the image level and the higher the grayscale resolution. On the contrary, the smaller the quantization level, the lower the grayscale resolution. The first picture below shows the image transformation as the sampling interval increases, and the second picture shows the lower the quantization level, the smaller the gray value.
- Image grayscale histogram
An image is composed of pixels with different gray values, and the distribution of gray in the image is an important feature of the image. The grayscale histogram of the image describes the grayscale distribution in the image, and can intuitively show how much each grayscale occupies in the image.
- Image enhancement
Mainly record the enhancement of the spatial domain.
1. Linear transformation and nonlinear transformation
2. Histogram trimming method. The gray histogram reflects the relationship between each gray level and its frequency of appearance in a digital image, and it can describe the general picture of the image. Histogram equalization is a method of passing the original image through a certain transformation to obtain a new image with a uniformly distributed grayscale histogram
