Image Compression using Vector Quantization

1. Image Compression using Vector Quantization Nopparat Pantsaena Manas Sangworasil Chinnapat Nantajiwakornchai Tanasak Phanprasit Research Center for Communication and Information Technology (ReCCIT) King Mongkut’s Institute of Technology Ladkrabang (KMITL) Bangkok, Thailand

2. Objective This research presents the Splitting solution to implement the Codebook, which improves the image quality by average Training Vectors and then splits the average result to Codebook that has minimum distortion.

3. Outline • Introduction • Codebook Design • Steps of LBG • Splitting Codebook design • Experimental and Result • Conclusion

4. Introduction Source Image Training Vector

5. Introduction Training Vector Codebook Design Codebook Table

6. Introduction New Image (Index Table) Codebook Table

7. Introduction ….(1) Block diagram of Vector Quantization Intro

8. Codebook Design • There are two kinds of Codebook • Random Codebook • Splitting Codebook

9. Comparison between Random and Splitting Codebook Design • Splitting has certain loops to find new codebook. • Splitting faster than Random algorithm. • Codebook’s size define by 2R. Random technique will not work if R is not an integer. But we can use the Spitting algorithm.

10. Codebook Design • Linde-Buzo-Gray’s Algorithm (LBG) xj(k)=[ xj(1) xj(2) xj(3)…xj(k) ] j = 1,2,3,…,n; n = number of the image parts k = vector dimension; (k=1,2,3,…,16)

11. Steps of LBG • Initial the value for Codebook Xi(k)=[(1)(2)(3)…(k)]; i=1,2,3,…,Nc Nc is number of vector in Codebook Back

12. Steps of LBG • Grouping the Training Vectors

13. Steps of LBG • P((k) ) = (Si; i=1,2,3,…,Nc); Si is the set of minimum distortion vectors • xj Si if • Minimum Distortion Values ….(2)

14. Steps of LBG • Average distortion • The average distortion can be calculated from each group, is given by ….(3)

15. Steps of LBG • Stop update the codebook if • And we can obtain the New Codebook

16. Steps of LBG • Otherwise, the process will continue update in the Codebook by average the group in 2nd step vectors as: ….(4)

17. Splitting Codebook design Split the Codebook to 2 vectors: and START Divide the image into small blocks Update Ym M=2M Arranging vector Ym={x1,x2,..xn} LGB Algorithm Set M=1 then Ym={x1 ,x2 ,..x16} Find centroid of vector by No M=Nc Yes END Keep Ym

18. Splitting Codebook design • From Training Vector, find the average of Training Vectors for setting the Codebook as follows k=1,2,3,…,16 n =1,2,3,…,16384 ….(5) Back

19. Splitting Codebook design • Split the Codebook to 2 vectors: ….(7) ….(6) j =1,2,3,…,Nc ni =1,2,3,…,16 Back

20. Splitting Codebook design • Split the Codebook to 2 vectors: Back

21. Experimental and Result • The value of PSNR is calculated from • RMSE when f(i,j) is the gray level of pixel i in the original image f(i,j)’ is the gray level of pixel i in the decompressed image. N is the total number of pixels in the image. ….(8) ….(9)

22. Experimental and Result Figure1. Lena

23. Experimental and Result Figure 2. Milk drop

24. Experimental and Result Figure 3. Mandrill

25. Experimental and Result Figure 4. Girl

26. Conclusion This paper proposed the implementation of Codebook to Vector Quantization image compression. From the experiment, the Split Codebook can achieve higher image quality than Random Codebook at the same bits rate. In another words, the proposed algorithm achieves lower bits rate at the same image quality

27. Thank youfor your attention.