The standard you choose can apply a method such as DCT to identify areas that overlap and eliminate extra data. There are a variety of compression standards you can use, depending on the desired outcome. For example, Huffman coding uses entropy coding methods while Discrete Cosine Transform (DCT) uses cosine functions to approximate signal frequencies. Compression techniques reduce these redundancies by eliminating or modifying image information. Within the image there are many pixels that display the same information, creating spatial redundancies. To understand how this works, consider any image. It reduces the size of files, making media easier to transfer and cheaper to store. Image and video compression enables you to deliver high-quality media with lower storage and bandwidth requirements. In this article, you will learn about different video and image compression techniques, the importance and role of codecs, and how machine learning algorithms are helping improve compression. However, it is only in recent years that the technology has matured. Artificial Intelligence (AI) has long been implemented for the purpose of improving compression.
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