Binary Arithmetic Coding System with Adaptive Probability Estimation by “Virtual Sliding Window” презентация

Binary Arithmetic Coding System with Adaptive Probability Estimation by “Virtual Sliding Window” Eugeniy Belyaev Marat Gilmutdinov Andrey Turlikov

Arithmetic Coding with Context Modeling

Sliding Window (Main Properties) W last processed symbols are used for probability estimation Buffer with W cells is used for keeping W last processed symbols. W is window length Frequencies of symbols are calculated basing on buffer content

Work of Encoder with Sliding Window Adaptation (Binary Case)

Work of Encoder with Sliding Window Adaptation (Binary Case)

Main Disadvantage of Sliding Window Method Using large size additional memory required for buffer of sliding window Necessity to store individual buffers with W cells for each context model Frequent context model changing is critical for memory cache Critical for DSP application

Chronology of Sliding Window Analysis

Imaginary Sliding Window (Main Properties) Using Randomized Finite State Machine with (W+1) states Method does not require to store buffer for previously processed data Random variable is used to estimate value of symbol xt-w removed from the sliding window

ISW (Main Algorithm) Step 1 and Step 2 are similar to classical sliding window algorithm (exception: ISW uses evaluation of St for probability estimation) Step 3: Modification of St evaluation.

Features of ISW Advantage Avoiding buffer usage Disadvantage Using generator of random values, synchronized on the encoder and decoder sizes

Avoiding Random Variable Usage

Integer Implementation of Virtual Sliding Window (VSW)

Advantages of VSW Virtual Sliding window method avoids buffer storage in memory; generation of random values; float-point operations with St calculation

Using VSW in H.264 Standard

Bitrate Savings for some Testing Video Sequences (in percent)