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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?

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?

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!!!

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!

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.

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.

Bit Allocation

• A constant bit rate does not result in constant quality.

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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”).

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

Bit Allocation

• A sneak peak at next week’s results …

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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.

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.

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.

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

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