  In the popular video coding trend, the encoder has the task to exploit both
spatial and temporal redundancies present in the video sequence, which is a
complex procedure. As a result almost all video encoders have five to ten times
more complexity than their decoders. In a video compression process, one of the
main tasks at the encoder side is motion estimation which is to extract the
temporal correlation between frames. Distributed video coding (DVC) proposed
the idea that can lead to low complexity encoders and higher complexity
decoders. DVC is a new paradigm in video compression based on the information
theoretic ideas of Slepian-Wolf and Wyner-Ziv theorems. Wyner-Ziv coding is
naturally robust against transmission errors and can be used for joint source
and channel coding. Side Information is one of the key components of the
Wyner-Ziv decoder. Better side information generation will result in better
functionality of Wyner-Ziv coder. In this paper we proposed a new method that
can generate side information with a better quality and thus better
compression. We have used HVS (human visual system) based image quality metrics
as our quality criterion. The motion estimation we used in the decoder is
modified due to these metrics such that we could obtain finer side information.
The motion compensation is optimized for perceptual quality metrics and leads
to better side information generation compared to con- ventional MSE (mean
squared error) or SAD (sum of absolute difference) based motion compensation
currently used in the literature. Better motion compensation means better
compression.
