(a) Why is file or data compression necessary for Multimedia activities? Multimedia files are very large therefore for storage file transfer etc file be reduced. Text and other files may also be encoded/compressed for email and other applications 2 MARKS--- BOOKWORK (b) Briefly explain, clearly identifying the differences between them, how entropy coding and transform coding techniques work for data compression. Illustrate your answer with a simple example ofeach type Compression can be categorised in two broad ways Lossless Compression where data is compressed and can be reconstituted(uncompressed) without loss of detail or information. These are referred to as bit-preserving or reversible compression systems also Lossy Compression where the aim is to obtain the best possible fidelity for a given bit-rate or minimizing the bit-rate to achieve a given fidelity measure. video and audio compression techniques are most suited to this form of compression Lossless compression frequently involves some form of entropy encoding and are based in information theoretic techniques ossy compression use source encoding techniques that may involve transform encoding, differential encoding or vector quantisation ENTROPY METHODS The entropy of an information source S is defined H(S)=SUM,(P Log2(1/P) where Pi is the probability that symbol S, in S will occur Log2(1/P)indicates the amount of information contained in Si, i.e., the number of bits needed to code S Encoding for the Shannon-Fano algorithm A top-down approach2. (a) Why is file or data compression necessary for Multimedia activities? Multimedia files are very large therefore for storage, file transfer etc. file sizes need to be reduced. Text and other files may also be encoded/compressed for email and other applications. 2 MARKS --- BOOKWORK (b) Briefly explain, clearly identifying the differences between them, how entropy coding and transform coding techniques work for data compression. Illustrate your answer with a simple example of each type. Compression can be categorised in two broad ways: Lossless Compression -- where data is compressed and can be reconstituted (uncompressed) without loss of detail or information. These are referred to as bit-preserving or reversible compression systems also. Lossy Compression -- where the aim is to obtain the best possible fidelity for a given bit-rate or minimizing the bit-rate to achieve a given fidelity measure. Video and audio compression techniques are most suited to this form of compression. Lossless compression frequently involves some form of entropy encoding and are based in information theoretic techniques Lossy compression use source encoding techniques that may involve transform encoding, differential encoding or vector quantisation. ENTROPY METHODS: The entropy of an information source S is defined as: H(S) = SUMI (PI Log2 (1/PI) where PI is the probability that symbol SI in S will occur. Log2 (1/PI) indicates the amount of information contained in SI, i.e., the number of bits needed to code SI. Encoding for the Shannon-Fano Algorithm: A top-down approach