1. Container.qcif @ 100 kbps

2. News.qcif @ 100 kbps

3. Current and Future Directions Class Histories –Are the significance probabilities of the coefficients in each class consistent across frames? –If so, can we take advantage of this? Bit Allocation –Currently, we assign the same number of bits to each frame, except possibly the first one. –Can we achieve better results by assigning a variable numbers of bits to each frame?

4. Current and Future Directions New Classes –Can we design a new set of classes which better reflects the statistical properties of motion-compensated video? Arithmetic Coding vs. Group Testing –What happens if we replace the Group Tester with an Arithmetic Coder?

5. Class Histories Recall that the optimal group test size is determined by the significance probability of the coefficients in the current class. As the Group Tester codes a class, it tracks the number of significant and insignificant coefficients seen so far. These numbers are used to determine the next test size. This is inefficient if the class contains few coefficients. By the time we learn the best size, we will be done coding the class!!!

6. Class Histories Question 1: Are the significance probabilities of the classes relatively consistent across frames? Answer: Yes! Especially recent frames. Question 2: Can we take advantage of this consistency? Answer: Yes!

7. Class Histories Algorithm sig[n] –A weighted measure of the number of significant coefficients seen in class n. insig[n] –a weighted measure of the number of insignificant coefficients seen in class n. weight –a parameter between 0 and 1 which determines how heavily to weight more recent frames.

8. Class Histories Algorithm Initialization –Let sig[n] := 0 for all classes n. –Let insig[n] := 0 for all classes n. Update(class n, sig coeffs sc, insig ic) –Let sig[n] := weight * (sig[n] + sc) –Let insig[n] := weight * (insig[n] + ic) Results from j frames ago will be scaled by (weight) j. Recall that weight < 1.

9. Bit Allocation A constant bit rate does not result in constant quality.

10. Bit Allocation We can measure the quality of individual frames with MSE (distortion) or PSNR (Peak Signal-to-Noise Ratio), but how do we measure the overall quality of the whole video? Method 1 (MMSE): Minimize the Mean MSE. Method 2 (MINMAX): Minimize the Maximum MSE. Leads to more constant quality, which is more visually appealing (less “flicker”).

11. Bit Allocation Advertisement for next week … I’ll be presenting my quals talk, which discusses two new bit allocation algorithms for embedded video coding (like GTV): –The MultiStage algorithm –The Ratio algorithm

12. Bit Allocation A sneak peak at next week’s results …

13. New Group Test Classes Recall that group testing is most effective when the coefficients in each class are independent and approximately equally likely to become significant. We want to redesign the classes come closer to this ideal. The history modification allows smaller classes to still be coded efficiently.

14. New Group Test Classes There is a correlation between the significance of corresponding coefficients in adjacent frames. Thus, the significance of the previous frame’s corresponding coefficient can be used as a classification criteria.

15. Bit Allocation There is also a correlation between the significance of the Y coefficients and the corresponding U and V coefficients. Thus, we can use this as a classification criteria as well.

16. Arithmetic Coding We currently use the Group Tester to encode each bit plane. What if we instead encoded the bit planes using an Arithmetic Coder? Advantages of Arithmetic Coding: –Simpler –More computationally efficient –Well known –Better performance when probabilities are close to 50%