Adaptive Edge-Based Side-Match Finite-State Classified Vector Quantization with Quadtree Map

1. Adaptive Edge-Based Side-Match Finite-State Classified Vector Quantization with Quadtree Map IEEE transactions on image processing. VOL. 5, NO. 2, FREBRARY 1996 Authors Ruey-Feng Chang(張瑞峰), CS, CCU Wei-Ming Chen(陳偉銘), CS, CCU

2. Outline • Introduction of Vector Quantization (VQ) • Basic VQ techniques • Adaptive edge-based side-match • Simulation results • Conclusion

3. Introduction of Vector Quantization (1/2) • Efficient scheme for image compression • Component • Codebooks • Generated by using the iterative clustering algorithm • Encoder • Image is first partitioned into non-overlapping rectangular blocks (vectors) • Each vector is quantized (indexed) to the closest codeword in the codebook • Decoder • Select the corresponding codeword in the codebook via indexes

4. Clustering algorithm Partition image to NxN blocks (vectors) Find the closet codeword and index for each vector Re-constructing image Find the corresponding codeword via indexes Training image set Target image Codebook Yi, i= 1, …, Nc Encoder side Decoder side

5. Introduction of Vector Quantization (2/2) • What is closest codeword • Small Euclidean distance • How to generate codebooks • Cluster algorithm • K-means • Linde-Buzo-Gray (LBG) • …

6. Basic VQ techniquesClassified Vector Quantization (CVQ) • Features • Multiple codebooks for specified features of blocks • Advantage • Reduce search time • Disadvantage • Extra bits needed

7. Basic VQ techniquesFinite-State Vector Quantization (FSVQ) • Features • Similar to CVQ, but the used codebook is decided by current codebook and current codeword • Advantage • Reduce search space • Extra bits aren’t needed • Disadvantage • Derailment

8. Basic VQ techniquesSide-Match Vector Quantization (SMVQ) (1/2) • Features • A class of FSVQ, but use the side of upper and left neighboring blocks to generate the state codebook • Advantage • Reduce search space • Smoother • Disadvantage • Derailment

9. Basic VQ techniquesSide-Match Vector Quantization (SMVQ) (2/2)

10. Adaptive edge-based side-match • Edge Detection • Sobel Filter • Classification • Non Edge Block (SMVQ) • Edge Block (CVQ,SMVQ)

11. Adaptive edge-based side-matchSobel Filter (1/2) • Sobel Filter can increase the high frequency part of image. • Formula • Gradient : • Θ : threshold for checking if the edge occur

12. Image region Mask used to compute Gx Mask used to compute Gy Adaptive edge-based side-matchSobel Filter (2/2) • Sobel operator • Gy = (z3 + 2z6 + z9) – (z1 + 2z4 + z7) • Gx = (z7 + 2z8 + z9) – (z1 + 2z2 + z3)

13. Adaptive edge-based side-matchQuadtree Map • Problem • Each vector need one more bit to determine its class • For example, in a 512 X 512 image with 4 X 4 block size, 16386 bits must be transmitted to the decoder • Solution • Quadtree map QTC=1-0011-0001-0011

14. Adaptive edge-based side-matchEdge Block(CVQ) • Nonedge blocks encode first. • Original SMVQ • The edge blocks are classified into 16 subclasses, according to the neighboring blocks which are edge or nonedge.

15. Adaptive edge-based side-matchEncode

16. Adaptive edge-based side-matchDecode

17. Simulation results (1/5) • Contribution • Higher quality with the same bit rate • Codebooks size are variable • Test arguments • 256 gray level image • Image size : 512 x 512 • Vector size : 4 x 4 • Test criterion

18. Simulation results (2/5)

19. Simulation results (3/5)

20. Simulation results (4/5)

21. Simulation results (5/5)

22. Conclusion • The classified FSVQ combine the advantages of CVQ and SMVQ • The system complexity is higher