Addressing the uncertainty in critical rate estimation for pixel-domain Wyner-Ziv video coding

Distributed video coding is typically treated as a channel coding problem among others. The encoder generates parity bits (or syndrome bits) for the source and transmits part of them to the decoder for a certain target quality. The decoder tries to reconstruct the source using the received parity bits along with the side information available. In this paper, we aim to estimate the critical number of parity bits to transmit. Having observed the uncertainty of the critical rate, we model it as a random variable, use its distribution to calculate the decoding failure probability and formulate the expected distortion. We allocate a certain bit budget among different bit-planes such that the expected distortion is minimized. Moreover, we introduce fast decoding at the encoder, which helps us to estimate the critical rate far more accurately. Eventually, we achieve up to 1.5 dB gain in rate-distortion performance at high bit rates.