Dpcm

DPCM - Overview
Principle of Differential Pulse Code Modulation (DPCM) Characteristics of DPCM quantization errors Predictive coding gain Adaptive intra-interframe DPCM Conditional Replenishment

Bernd Girod: EE398B: Image Communication II

DPCM no. 1

Principle of DPCM input s + e quantizer + s predictor + s' e' entropy coder channel

coder

output

s' + predictor s

+ e'

entropy decoder

channel

decoder

Prediction error

Reconstruction

Reconstruction error = quantization error

e= s−s ˆ

s ′ = e′ + s ˆ

s′ − s = e′ − e = q
DPCM no. 2

Bernd Girod: EE398B: Image Communication II

Quantization error feedback in the DPCM coder
Assuming a linear predictor, the DPCM coder is equivalent to the following structure: ~ s + e e quantizer e' predictor s (s) s (q) predictor q (e) +

Transfer function of the prefilter:

˜ E (Ω) = [1 − P(Ω)]S(Ω)

Ω - abbreviation for frequency vector, ω e.g., ( x , ω y )

transfer function of the predictor

Transfer function of quantization error feedback:

˜ E ′(Ω) = E(Ω) + [1 − P(Ω)]Q(Ω)
Bernd Girod: EE398B: Image Communication II DPCM no. 3

Power spectrum of the DPCM quantization error
Power spectral density of the quantization error q measured for intraframe DPCM with a 16 level quantizer

π
−π
0
0

ωx

ωy

π −π

Bernd Girod: EE398B: Image Communication II

DPCM no. 4

Signal distortions due to intraframe DPCM coding
Granular noise: random noise in flat areas of the picture Edge busyness: jittery appearance of edges (for video) Slope overload: blur of high-contrast edges, Moire patterns in periodic structures.

Bernd Girod: EE398B: Image Communication II

DPCM no. 5

Example of intraframe DPCM coding

1 bit/pixel prediction error coding slope overload

2 bit/pixel edge busyness granular noise

3 bit/pixel

Linear predictor:

0 1/2

1/4 1/4

4 bit/pixel

original

Lloyd-Max quantizers Fixed-length coding
DPCM no. 6

Bernd Girod: