Scalar and Vector Quantization

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Midrise vs. Midtread Quantizer Midrise Midtread 12/55
Uniform <strong>Quantization</strong> of Uniform Source If the source is uniformly distributed in [–X max , X max ], the output is quantized by an M-level uniform quantizer, then the quantization step size is <strong>and</strong> the distortion is ∆ = 2X max M , σ M / 2 2 2 i∆ 2 ⎛ 2i −1 ⎞ 1 ∆ = 2∑∫ q ⎜ x − ∆⎟ dx = ( i−1) ∆ i= 1 ⎝ 2 ⎠ 2X max 12 . This is quite difficult to evaluate! 13/55
Page 1 and 2: Scalar and Vector Quantization Nati
Page 3 and 4: The Quantization Problem Encoder m
Page 5 and 6: Quantization Function A quantizer
Page 7 and 8: Quantization Error If the quantiza
Page 9 and 10: Quantized Bitrate with VLC For VLC
Page 11: Uniform Quantizer All intervals ar
Page 15 and 16: The SNR of Quantization For n-bit
Page 17 and 18: Quantization of Non-uniform Sources
Page 19 and 20: Solving for Optimum Step Sizes Giv
Page 21 and 22: Variance Mismatch Effects (1/2) Ef
Page 23 and 24: Distribution Mismatch Effects Give
Page 25 and 26: Forward Adaptive Quantization (FAQ)
Page 27 and 28: Speech Quantization Example (2/2)
Page 29 and 30: Backward Adaptive Quantization (BAQ
Page 31 and 32: Output Levels of 3-bit Jayant Quant
Page 33 and 34: Picking Jayant Multipliers We must
Page 35 and 36: Jayant Quantizer Performance To av
Page 37 and 38: pdf-optimized Quantization Given f
Page 39 and 40: Lloyd-Max Algorithm (2/3) Begin wi
Page 41 and 42: Example: pdf-Optimized Quantizers
Page 43 and 44: Companded Quantization (CQ) In com
Page 45 and 46: Example: CQ (2/2) The expandar fun
Page 47 and 48: Entropy Coding of Quantizer Outputs
Page 49 and 50: Why Vector Quantization (1/2)? Cor
Page 51 and 52: Vector Quantization Rule Vector qu
Page 53 and 54: The Linde-Buzo-Gray Algorithm 1. St
Page 55: Impact of Training Set The trainin

Scalar and Vector Quantization

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