MMC VTU Notes

Hi I am interested in having some of the notes for the Multimedia topic for the Electronics & Communication Engineering discipline for VTU?

[Rajkumar Agarwal]

Some of the notes for the Multimedia topic for the Electronics & Communication Engineering discipline for VTU has been mentioned below:

Multimedia Applications – in pressure is applied Compression: Technique, which is initially connected to the source data before its transmission Compression done to:1.

Decrease the volume of data to be transmitted – content, fax, and images2.

Lessen the data transmission – required for the transmission of discourse, sound, and video

Pressure Principles

Pressure calculations – taking into account the accompanying pressure principles1.

Source encoders and destination decoders2.

Lossless and lossy compression3.

Entropy encoding4.

Source encoding

1. Source encoders and destination decoders

Pressure calculation – is connected to the source data – identifying with a specific sight and sound application – earlier to transmitting Matching decompression calculation – must be connected – to replicate the first source data or an almost exact copy of it

Source encoder:

Utilized for the use of the pressure calculation

Destination decoder:

Utilized for the use of decompression calculation

Two PCs – conveying cases in: Time required to perform – the pressure and decompression – is not generally basic – so

Both calculations: Implemented in programming – inside the two computersTime required to perform – the pressure and decompression – is not generally criticalOther correspondence cases in: Compression and decompression calculation in programming shapes – is not acceptableTwo calculations – here, must be performed – by unique processors in isolated units

2. Lossless and lossy pressure

Pressure calculations – can be lossless or lossy

Lossless pressure algorithm: Aim

– lessen the measure of source data – to be transmitted – in a manner that – destination in, when decompressed – there is no loss of informationReversible pressure – another name of lossless pressure

Ex.:
Content document – exchange over the system – no, part of the source data is lost – amid either the pressure or decompression operations

Lossy pressure algorithm: Aim

– typically, not to deliver the precise of the source data after decompression – at the same time, a rendition of it which is seen by the beneficiary as a genuine copySuch applications – in higher the level of pressure being connected to the source data – the more approximate– the got variant gets to be

Ex.:
Exchange of digitized pictures and sound and video streamsIn such cases: affectability of the human eye or ear – is such that – any fine points of interest, might miss from the originalsource signal after decompression – are not distinguished

3. Entropy encoding

Is lossless Independent of the kind of the data – that is being compressed Concerned exclusively with how the data is spoken to

Case of entropy encoding:

1. Run-length encoding and 2. Factual encoding Applications – in either the one of above or both – are utilized