Image and Video Coding

The information content within images and video may be compressed to reduce the volume of data for storage, reduce the bandwidth required to transmit data from one point to another (for example over a network), or minimise the power required by the system (both for compression and data transmission). Compression is only possible because images contain significant redundant information. There are at least four types of redundancy within images that can be exploited for compression: spatial redundancy, temporal redundancy, spectral redundancy, and psychovisual redundancy. A codec (coder–decoder) can be categorised as either lossless or lossy. The discrete cosine transform is close to the optimal linear transform for decorrelating the pixel values. This enables it to concentrate the energy into a few components, making it an obvious choice for image compression. The wavelet transform is used primarily to decorrelate the data. Many of the image compression standards also provide a lossless compression option.