Fast vector quantization image coding by mean value predictive algorithm Authors: Yung-Gi Wu, Kuo-Lun Fan Source: Journal of Electronic Imaging 13(2), 324–333 (April2004). Speaker: Meng-Jing Tsai Date:

Outline Introductions – Vector Quantization (VQ) – Accelerate Coding Techniques Partial Distance Search (PDS) Algorithm Fast Euclidean Computation Technique Proposed Coding Scheme – Preprocessing process – Practical Encoding Process Simulation Results Conclusions 2

Training set N-2 N-1 Introduction - VQ LBG Algorithm Initial codebook Training Images 3

Introduction - VQ Image encoding procedure Image Index table w h 4

Introduction - VQ Image decoding procedure Image Index table w h 5

Introduction – VQ & PDS The traditional VQ compression system must search from the first codeword to the last one. It costs a lot of time. In order to accelerate the computation, the PDS algorithm provides an effective coding technique. 6

c 10 c 11 c 12 c 13 c 115 c 00 c 01 c 02 c 03 c 015 Introduction - PDS c 20 c 21 c 22 c 23 c 215 v0v0 v1v1 v2v2 v3v3 v4v4 v5v5 v6v6 v7v7 v8v8 v9v9 v 10 v 11 v 12 v 13 v 14 v 15 Codebook Vector ＝ d min d > d min ＝ d min d < d min 7

Introduction Fast Euclidean Computation Technique  Look-up Table (LUT) 8

Proposed Coding Scheme Two parts  Preprocessing process 1.A codebook that is sorted by the mean value of each codeword within the codebook. 2.The sorted mean value table of each codeword. 3. The 2D fast Euclidean table.  Practical encoding process 9

Proposed Coding Scheme Pratical Encoding Process mean = st codeword 2 nd codeword (FSP-1) th codeword First Search Point (FSP) codeword (FSP+1) th codeword th codeword 255 th codeword mean value table codebook 10

Practical Encoding Process PSNR = dB 11

Pratical Encoding Process The searching direction. 12

Simulation Results First situation – codebook1 & Lenna Second situation – codebook2 & Jet, Pepper, Lenna, and Scene 13

Simulation Results First situation PSNR and window size (codebook1 and 2D fast Euclidean technique) PSNR and window size (codebook1 and 1D fast Euclidean technique) 14

Simulation Results First situation 15

Simulation Results First situation 16

Simulation Results First situation The average arithmetic operation for each pixel needed with the codebook1. 17

Simulation Results Second situation – codebook2 and 2D fast Euclidean technique Window size and CPU timeWindow size and PSNR 18

Simulation Results Second situation The average arithmetic operation for each pixel needed with the codebook2. 19

Conclusions The PDS algorithm and the (2D) fast Euclidean technique are used to accelerate the calculation. It needs more memory for extra tables. Compared to a full search algorithm, it saves more than 95% searching time. 20

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