Digitization Principles (1)

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Multimedia information

representation

Characters represented as Code word

Images as lines, lines as coordinates, coordinateas a pair of digital value.

Microphones , video cameras electrical signalsof varying amplitude

Amplitude is magnitude or image intensity

Analog signal

Conversion into digital form-signal encoder.



Digitization Principles

Analog signal

Varying amplitude

Fourier analysis Signal bandwidth

Band limiting channel



Encoder Design

Conversion of time varying analog signal by signalencoder(electronic circuit)

The principles of an encoder

Band limiting filter

Analog to digital converter(ADC) consisting of sample andhold , quantizer circuit.

The bandlimiting filter removes selected higherfrequency components from source signal

Sample and hold

samples the amplitude of the filtered signal at regular

intervals of time



Holds the sample amplitude constant between thesamples

Quantizer converts each amplitude into a binary

value known as code word.

The most significant bit of each code wordindicates the polarity sign of the sample

Positive value by 0

Negative value by 1

Both are relative to zero level



Sampling rate

Nyquist sampling theorm

To obtain an accurate representation of a time varyinganalog signal its amplitude must be sampled at a

minimum rate that is greater or equal to twice the highest frequency component present in the signal.

This is known as Nyquist rate represented as eitherHz or samples per second (sps)

Sampling at a rate lower than Nyquist rate results inadditional frequency component being generatedwhich distorts the original signal



In practice the transmission channel used haslower bandwidth than the source signal.

To avoid distortion the bandwidth and hence thefrequency range of the transmission channeldetermines the sampling rate rather than thebandwidth of the original signal

In such cases the source signal may have higherfrequency components than the nyquist rate

It becomes essential to pass the source signalthrough band limiting filter



Quantization Intervals

To represent the amplitudes in a digital format it would require an infinite number of binary digits.

When a finite number of digits are used eachsample is represented by a correspondingnumber of discrete levels.

In the example three bits are representing each

sample including the sign bit. The result is four positive and four negative

quantization intervals.



If Vmax is the maximum positive and negative signalamplitude and n is the number of binary bits usedthen the magnitude of each quantization interval q

is

q=2Vmax /2n

The signal anywhere in the interval will be

represented by same binary codeword Each code word corresponds to a nominal

amplitude level which is at the center of the interval

The actual signal level may differ by q/2(+ or -)



The difference between the actual andcorresponding amplitude is called quantizationerror.

The error value varies randomly from sample tosample hence is also known as quantization noise.

Another factor influencing the choice of number of

quantization intervals is smallest amplituderelative to peak amplitude.

The ratio of smallest amplitude to peak is called asdynamic range of the signal D ,scale as decibels or

db.



D=20 log10(Vmax/Vmin)db

It is essential to ensure that the level of quantization noise relative to the smallest signalamplitude is acceptable.



Decoder Design

The analog signal signals are stored ,processedand transmitted in a digital form

Prior to their output they need to be convertedback.(loud speakers)

The electronic circuit that performs this conversionoperation is known as a signal decoder.

The principles for it are Digital to analog convertor (DAC)

Low pass filter (recovery or reconstruction filter

Most multimedia applications involving audio and

viedo the communication channel is a two way



Hence audio/video encoder and decoder arecombined into a signal unit called audio/videocodec or encoder-decoder.

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Digitization Principles (1)