Image processing is to convert an image into a digital matrix, store it in a computer and process it with a certain algorithm. The basis of image processing is mathematics, and the most important task is the design and implementation of various algorithms. At present, image processing technology has been widely used in communication technology, remote sensing technology, biomedicine, industrial production, computer science and many other aspects. According to the different requirements of application fields, image processing technology can be divided into many branches, the most important of which are: ① image digitization: converting analog images into digital forms that are convenient for computer processing through sampling and quantization; ③ Image enhancement and restoration: The main purpose is to enhance the useful information in the image, weaken the interference and noise, and make the image clear or transform it into a form more suitable for analysis; ③ Image coding: The image is coded under a certain fidelity condition to achieve the purpose of compressing the image information, simplifying the image and facilitating storage and transmission. ④ Image reconstruction: mainly use the collected data to reconstruct the image. The main algorithms of image reconstruction include algebra, Fourier backprojection and convolution backprojection. ⑤ Pattern recognition: Recognition is the main purpose of image processing. For example, fingerprint recognition and face recognition are the contents of pattern recognition. Today, there are usually three pattern recognition methods: statistical recognition, syntactic structure pattern recognition and fuzzy recognition.