1. Lossless
coding and lossy coding
1.1. Self-information
and entropy.
1.2. Symbol
emission frequencies.
1.3. Huffman
codes.
1.4. Differential
entropy and mutual information.
1.5. The
fundamental lossy coding problem: Rate and distortion. Distortion measures.
Algorithms and complexity.
1.6. Sampling
theorem. Sampling oftwo-dimensional
signals and moving pictures.
1.7. Lossless
coding of sequences of symbols: Arithmetic coding.
2. Quantization
2.1. Quantizing
notions: sample, input-output characteristic, quantization error.
2.2. Uniform
quantizer: input-output characteristic types, quantization regions.
2.3. Statistic
model for quantization error.
2.4. Nonuniform
quantizers: compressor, expander, A and
µ companding laws.
2.5. Training
vector quantizers: Linde-Buzo-Gray (LBG) algorithm.
2.6. Pulse
code modulation (PCM) of speech, audio and video signals.
3. Adaptive
quantization
3.1. Short-term
energy: blockwise estimation and recursive estimation.
3.2. Estimation
modes for the parameters of an adaptive quantizer: feed-forward estimation
and feedback estimation.
3.3. Quantizer
step-size adaptation.
3.4. Adaptive
gain control of input signal.
4. Fixed
prediction with adaptative quantization
4.1. Differential
signal and prediction-quantization loop.
4.2. Basic
differential PCM (DPCM), prediction gain.
4.3. Long-term
spectrum of speech signals and autocorrelation models for images.
4.4. Prediction
applied to lossless image coding.
4.5. Adaptive
DPCM (ADPCM) and adaptation logics.
4.6. Delta
modulation.
5. Linear
prediction
5.1. Predicting
the speech signal
based on its short-term spectrum.
5.2. Variable
predictor.
5.3. Predictive
analysis.
6. Adaptive
predictive coding
6.1. APC
with feedback or feed-forward adaptive prediction.
6.2. Adaptive
prediction coders with a long-term predictor.
6.3. Noise
feedback coding.
6.4. Residual-excited
linear predictive coder.
6.5. Vector
representation of the excitation signal.
6.6. Code-excited
linear predictive (CELP) coder.
7. Transform
coding
7.1. Transforms
and base vectors or base matrices.
7.2. Transform
gain.
7.3. Karhunen-Loève
transform (KLT).
7.4. Discrete
cosine transform (DCT).
7.5. Quantizing
and coding transform coefficients: bit allocation, zonal sampling, zigzag
scanning, run-length encoding (RLE) and
Huffman coding.
7.6. The
Joint Photographic Experts Group (JPEG) still image coder.
8. Subband
coding
8.1. Subband
coding (SBC): principles and comparison with transform coding(AT)
as a special case.
8.2. Downsampling
and upsampling.
8.3. Perfect
reconstruction.
8.4. Quadrature-mirror
filter (QMF) bank.
8.5. Subband
coding gain.
8.6. Bit
allocation among the subbands based on the power spectrum of the signal.
8.7. Tree-structured
filter banks.
8.8. Aural
masking: Signal-to-mask ratio (SMR), noise-to-mask ratio (NMR), masking
thresholds.
8.9. Moving
Pictures Expert Group (MPEG) audio coding.
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