1. Low Complexity Scalable DCT Image Compression IEEE International Conference on Image Processing 2000 Philips Research Laboratories, Eindhoven, Netherlands Rene J. van der Vleuten, Richard P.Kleihorst, Christian Hentschel

2. Outline  Common Bit Plane Coding Technique  New Bit Plane Coding Technique  Algorithm Description by Example  Experimental Result  Complexity Analysis  Conclusion

3. Common Bit Plane Coding Technique

4. New Bit Plane Coding Technique Significant Coefficient: 1 in any higher bit planes (encoded) Insignificant Coefficient: 0 in all higher bit planes Newly Significant Coefficient: 1 in the current bit plane

5. Algorithm Description by Example 1 +1 1 0 0 The 64 coefficients of 8 * 8 image block after discrete cosine transform: 20, 3, 0, -5, 0, 0, 0, 0, -2, 0, 0, 0, ……, 0 (DC coefficients from all blocks are collected and put into the bit string before AC coefficients.)

6. Bit Plane 1 Coding 00010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign significant coefficient table

7. Bit Plane 1 Coding 00010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 1 position12345678…63 sign significant coefficient table

8. Bit Plane 1 Coding 00010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 1000 position12345678…63 sign significant coefficient table RMAX 

9. Bit Plane 1 Coding 00010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 1000011 position12345678…63 sign significant coefficient table CMAX 

10. Bit Plane 1 Coding 00010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 10000110 position12345678…63 sign significant coefficient table

11. Bit Plane 1 Coding 00010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 100001100 position12345678…63 sign significant coefficient table

12. Bit Plane 1 Coding 00010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 10000110011 position12345678…63 sign1 significant coefficient table

13. Bit Plane 2 Coding 01000000 10000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign1 significant coefficient table

14. Bit Plane 2 Coding 01000000 10000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign1 significant coefficient table 0

15. Bit Plane 2 Coding 01000000 10000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign1 significant coefficient table 0101

16. Bit Plane 2 Coding 01000000 10000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign1 significant coefficient table 01001001

17. Bit Plane 2 Coding 01000000 10000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign01 significant coefficient table 0100100110

18. Bit Plane 2 Coding 01000000 10000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign011 significant coefficient table 010010011011

19. Bit Plane 2 Coding 01000000 10000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign011 significant coefficient table 0100100110110

20. Bit Plane 3 Coding 01010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign011 significant coefficient table

21. Bit Plane 3 Coding 01010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign011 significant coefficient table 1

22. Bit Plane 3 Coding 01010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign011 significant coefficient table 11

23. Bit Plane 3 Coding 01010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign011 significant coefficient table 110

24. Bit Plane 3 Coding 01010000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 position12345678…63 sign011 significant coefficient table 1100

25. Experimental Result

26. Complexity Analysis

27. Conclusion  Scalable Image Compression –Bit-rate or Quality Scalability –Real-time Adaptation to Wire or Wireless Channels  Adaptive Signal-dependent Rectangular Zone –DCT block often has a bias for either the horizontal or vertical direction. –It produces more efficient than signal-independent zig- zag scan.  Lower Complexity with Good Performance: –No Quantization –No Entropy Coding (Huffman or Arithmetic Coding)