Distributed video coding (DVC) has attracted a lot of attention during the past decade as a new solution for video compression where the computationally most intensive operations are performed by the decoder instead of by the encoder. One very important issue in many current DVC solutions is the use of a feedback channel from the decoder to the encoder for the purpose of determining the rate of the coded stream. The use of such a feedback channel is not only impractical in storage applications but even in streaming scenarios feedback-channel usage may result in intolerable delays due to the typically large number of requests for decoding one frame. Instead of reverting to a feedback-free solution by adding complexity to the encoder for performing encoder-side rate estimation, as an alternative, in previous work we proposed to incorporate constraints on feedback channel usage. To cope better with rate fluctuations caused by changing motion characteristics, in this paper we propose a refined approach exploiting information available from already decoded frames at other temporal layers. The results indicate significant improvements for all test sequences (using a GOP of length four).
Distributed video coding is a new video coding paradigm that shifts the computational intensive motion estimation
from encoder to decoder. This results in a lightweight encoder and a complex decoder, as opposed
to the predictive video coding scheme (e.g., MPEG-X and H.26X) with a complex encoder and a lightweight
decoder. Both schemas, however, do not have the ability to adapt to varying complexity constraints imposed by
encoder and decoder, which is an essential ability for applications targeting a wide range of devices with different
complexity constraints or applications with temporary variable complexity constraints. Moreover, the effect of
complexity adaptation on the overall compression performance is of great importance and has not yet been investigated.
To address this need, we have developed a video coding system with the possibility to adapt itself to
complexity constraints by dynamically sharing the motion estimation computations between both components.
On this system we have studied the effect of the complexity distribution on the compression performance.
This paper describes how motion estimation can be shared using heuristic dynamic complexity and how
distribution of complexity affects the overall compression performance of the system. The results show that the
complexity can indeed be shared between encoder and decoder in an efficient way at acceptable rate-distortion performance.