Current interframe video compression standards such as the MPEG4 and H.264, require a high-complexity encoder for predictive coding to exploit the similarities among successive video frames. This requirement is acceptable for cases where the video sequence to be transmitted is encoded once and decoded many times. However, some emerging applications such as video-based sensor networks, power-aware surveillance and mobile video communication systems require computational complexity to be shifted from encoder to decoder. Distributed Video Coding (DVC) is a new coding paradigm, based on two information-theoretic results, Slepian-Wolf and Wyner-Ziv, which allows exploiting source statistics at the decoder only. This architecture, therefore, enables very simple encoders to be used in video coding. Wyner-Ziv video coding is a particular case of DVC which deals with lossy source coding where side information is available at the decoder only. In this thesis, we implemented a DVC codec based on the DISCOVER (DIStributed COding for Video sERvices) project and carried out a detailed analysis of each block. Several algorithms have been implemented for each block and results are compared in terms of rate-distortion. The implemented architecture is aimed to be used as a testbed for future studies.