"Visually lossless" means that the displayed image will appear identical to the original image, even if some data may actually have been lost during compression. The displayed image is identical to the original source image. "Lossless" refers to a compression method in which there is no loss of data during the transmission of a video signal from source to display. Types of compression are often categorized by the amount of data that’s maintained through the stages of processing. Different video compression standards utilize different methods of reducing data, and hence, results may differ in bit rate (i.e. The process for encoding and decoding must be matched video content that is compressed using one standard cannot be decompressed with a different standard. The time it takes to compress, send, decompress and ultimately display a stream is known as latency.Ī video codec (encoder/decoder) employs a pair of algorithms that work together. To decode (play) the compressed stream, an inverse algorithm is applied. An encoding algorithm is applied to the source video to create a compressed stream that is ready for transmission, recording, or storage. Video compression is a process that reduces and removes redundant video information so that a digital video file/ stream can be sent across a network and stored more efficiently. This example illustrates why video compression technology is often necessary when working with digital signals in these contexts. At a frame rate of 60 fps, just one second of this video results in 3.6 GB of data, which is impractical for most current networks and storage systems. For example, an image size of 1920x1080 pixels at 24 bit color depth can translate to about 6 MB per frame. The rise of digital technology has introduced a new set of challenges, primarily related to the vast amount of data that is required to represent digital video. Digital technologies and networks have made these tasks significantly more effective than was ever possible in the analog domain. Information from any number of content sources frequently must be shared with co-workers who may be located in the same room or in remote locations around the globe. One of the most important differences between these two types of applications is that professional/ commercial users don’t just use content like consumers do rather, they often need to work with, manipulate, and combine this content with other sources. These requirements become especially challenging when audio and video signals are involved, because massive amounts of data are necessary to translate the characteristics of sound and light into bits.ĭigital sound and video have created entirely new industries for both consumer and professional/commercial applications. However, representing information as groups of binary numbers requires an enormous amount of computing power, specifically memory capacity and processing capability. Digital technologies have revolutionized the way we work with both audio and video signals.
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