What is the purpose of image transformation? What are the commonly used image transformation algorithms?

The purpose of image transformation is to process and analyze images quickly and effectively. It is necessary to transform the image originally defined in the image space into another space in some form, use the unique properties of this space for convenient processing, and finally transform it back into the image space to get the desired effect.

Image transformation is a summary of image processing algorithms, which can be divided into four parts: equal dimension algorithm of spatial transformation, variable dimension algorithm of spatial transformation, variable dimension algorithm of range transformation and variable dimension algorithm of range transformation.

Among them, the spatial transformation mainly refers to the geometric transformation of the image, while the range transformation mainly refers to the transformation of the image in pixel values. Isodimensional transformation is in the same dimensional space, and variable dimensional transformation is in different dimensional spaces, such as two-dimensional to three-dimensional, gray space to color space.

Extended data:

Related extensions: picture introduction

2 1 century is an era full of information. As the visual basis for human beings to perceive the world, images are an important means for human beings to obtain information, express information and transmit information. Digital image processing, that is, using computers to process images, has a short history. Digital image processing technology originated in the 1920s. A photo was transmitted from London, England to new york, USA by submarine cable, and digital compression technology was adopted.

First of all, digital image processing technology can help people understand the world more objectively and accurately, while human visual system can help people get more than 3/4 information from the outside world. Images and graphics are the carriers of all visual information, although the human eye has high resolution.

Thousands of colors can be recognized, but in many cases, the image is blurred and even invisible to the human eye. Through image enhancement technology, blurred or even invisible images can be made clear and bright.

In computer, images can be divided into four basic types according to the number of colors and grayscales: binary images, grayscale images, index images and true color RGB images. Most image processing software supports these four types of images.

China Internet of Things School-Enterprise Alliance believes that image processing will be one of the important pillars of the development of the Internet of Things industry, and its specific application is fingerprint identification technology.

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