Compare lossy compression and lossless compression

The concept of image compression

Image compression is the application of data compression techniques to digital images, aiming to reduce redundant information in image data, so as to store and transmit data in a more efficient format.

The basic principles of image compression

Remove redundant data. From a mathematical perspective, this process is essentially transforming a two - dimensional pixel array into a statistically uncorrelated data set.Image compression refers to the technology of representing the original pixel matrix with fewer bits, either lossy or lossless, and is also known as image encoding.The reason why image data can be compressed is the existence of redundancy in the data. The redundancy of image data is mainly manifested in the following ways: spatial redundancy caused by the correlation between adjacent pixels in the image; temporal redundancy caused by the correlation between different frames in the image sequence; and spectral redundancy caused by the correlation between different color planes or spectral bands. The purpose of data compression is to reduce the number of bits required to represent the data by removing this data redundancy. Due to the huge amount of image data, it is very difficult to store, transmit, and process. Therefore, the compression of image data is of great importance.

Basic methods of image compression

Image compression can be either lossy data compression or lossless data compression. For technical drawings, charts, or comics, lossless compression is preferred, as lossy compression methods, especially at low bitrates, will introduce compression distortion. For valuable content such as medical images or scanned images for archiving, lossless compression methods should also be selected as much as possible. Lossy methods are well - suited for natural images. For example, in some applications, a small loss of the image is acceptable (and sometimes imperceptible), which can significantly reduce the bitrate.