Multimedia compression is a broad term that refers to the compression of any type of multimedia (i.e. combination of media and content forms), most notably graphics, audio, and video. Multimedia actually derives from data sampled by a device such as a camera or a microphone. Such data contains large amounts of random noise, thus, traditional lossless compression algorithms tend to do a poor job compressing multimedia. Multimedia compression algorithms, traditionally known as codecs, work in a lossy fashion and the entire process is known as transform coding.
The term Transform coding is a technique for compressing signals such as audio signals (1-D) or images (2-D). In transform coding, a frequency transform or other basic transformation is applied before entropy coding. The inverse transformation is applied after decoding. This has a considerable benefit since it produces coefficients that have a statistically significant distribution which can be modelled and compressed more easily.
3.2 CATEGORIES OF MULTIMEDIA COMPRESSION
Multimedia compression can be broadly classified as Lossless and Lossy compression.
3.2.1 LOSSY COMPRESSION
In information technology, “lossy” compression is a data encoding method which discards some of the data, in order to achieve its goal, with the result that decompressing the data yields content that is different from the original, though similar enough to be useful in some way.
Lossy compression is most commonly used to compress multimedia data (audio, video, still images), especially in applications such as streaming media and internet telephony. Lossy compression formats suffer from generation loss: repeatedly compressing and decompressing the file will cause it to progressively lose quality. Information theoretical foundations for lossy data compression are provided by rate distortion theory.
There are two basic lossy compression schemes:
In lossy transform codecs, samples of picture or sound are taken, chopped into small segments, transformed into a new basis space, and quantized. The resulting quantized values are then entropy coded.
In lossy predictive codecs, previous and/or subsequent decoded data is used to predict the current sound sample or image frame. The error between the predicted data and the real data, together with any extra information needed to reproduce the prediction, is then quantized and coded.
In some systems, the two techniques are combined, with transform codecs being used to compress the error signals generated by the predictive stage.
3.2.2 LOSSLESS COMPRESSION
Lossless compression is a compression technique that does not lose any data in the compression process. This compression “packs data” into a smaller file size by using a kind of internal shorthand to signify redundant data. If an original file is 1.5MB, lossless compression can reduce it to about half that size, depending on the type of file being compressed. This makes lossless compression convenient for transferring files across the Internet, as smaller files transfer faster.
Lossless compression is also handy for storing files as they take up less room. The zip convention, used in programs like WinZip, uses lossless compression. For this reason zip software is popular for compressing program and data files. That’s because when these files are decompressed, all bytes must be present to ensure their integrity. If bytes are missing from a program, it won’t run. If bytes are missing from a data file, it will be incomplete and garbled. GIF image files also use lossless compression.
Lossless compression has advantages and disadvantages. The advantage is that the compressed file will decompress to an exact duplicate of the original file, mirroring its quality. The disadvantage is that the compression ratio is not all that high, precisely because no data is lost are missing from a program, it won’t run. If bytes are missing from a data file, it will be incomplete and garbled. GIF image files also use lossless compression.
3.3 LOSSY VERSUS LOSSLESS COMPRESSION
Lossless and lossy compressions have become part of our every day vocabulary largely due to the popularity of MP3 music files. A standard sound file in WAV format, converted to an
MP3 file will lose much data as MP3 employs a lossy, high-compression algorithm that tosses much of the data out. This makes the resulting file much smaller so that several dozen MP3 files can fit, for example, on a single compact disk, verses a handful of WAV files. However the sound quality of the MP3 file will be slightly lower than the original WAV.
The advantage of lossy methods over lossless methods is that in some cases a lossy method can produce a much smaller compressed file than any lossless method, while still meeting the requirements of the application.
Lossy methods are most often used for compressing sound, images or videos. This is because these types of data are intended for human interpretation where the mind can easily “fill in the blanks” or see past very minor errors or inconsistencies – ideally lossy compression is transparent (imperceptible), which can be verified via an ABX test.
3.4 PRINCIPLES OF VIDEO COMPRESSION
The principle of still image compression is very similar to that of video compression. In principle, one way to compress video source is to apply any of the common algorithms such as JPEG algorithm independently to each frame that makes up a video. This approach is also known as moving JPEG or MPEG. For now typical compression ratios of about 29:1 obtained with JPEG are not large enough to produce the compression ratio needed for multimedia applications.
In practice, in addition to the spatial redundancy present in each frame considerable redundancy is often present between a set of frame since only a small portion of each frame is involved with any motion that is taking place. For an example, consider the movement of a person’s lip or eye in a video telephony application.
3.5 APPLICATION OF MULTIMEDIA COMPRESSION
Video (and audio) need to be compressed in practice for the following reasons:
Uncompressed video (and audio) data are huge. In HDTV, the bit rate easily exceeds 1 Gbps and this poses a big problem for storage and network communications. As can be seen, restriction in data rate means that the original signal must be compressed. It is really impressive to note that the intent is to deliver very high quality video to the end user, with as few visible artefacts as possible.
Lossy methods have to be employed since the compression ratio of lossless methods is not high enough for image and video compression, especially when distribution of pixel values is relatively flat. The following compression types are commonly used in Video compression:
· Spatial Redundancy Removal – Intraframe coding (JPEG)
· Spatial and Temporal Redundancy Removal – Intraframe and Interframe coding (H.261, MPEG).
Multimedia compression can be broadly classified as Lossless and Lossy compression. In information technology, “lossy” compression is a data encoding method which discards some of the data, in order to achieve its goal, with the result that decompressing the data yields content that is different from the original, though similar enough to be useful in some way while Lossless compression is a compression technique that does not lose any data in the compression process.
SELF ASSESSMENT EXERCISE
Discuss the advantage of a lossy method over the lossless method of compression.
In this unit you have learnt about Multimedia Compression and its features. You have also
learnt that there different applications of multimedia compression.
6.0 TUTOR MARKED ASSIGNMENT
What are the comparative features between the two categories of Multimedia Compression?
Explain the application of multimedia Compression.
What do you understand by the principle of Video Compression?