Distributed video coding paradigm aims at transferring the major part of the processing computation effort from the encoder to the decoder. Motion interpolation is done at the decoder to generate side information (SI) through motion compensated temporal interpolation (MCTI). SI is considered as a noisy version of the original data: channel control coding schemes, such as turbo coding, are used to eliminate the errors (SI inaccuracies). The video data is turbo encoded and the parity bits are sent to the decoder. The systematic bits, however, are discarded since the decoder already disposes of SI that can be used for the channel likelihood ratio calculations. However, when the MCTI generation of SI is highly corrupted, the channel likelihood ratios based on the SI are inefficient and even misleading. A number of parity bits number exceeding the original data length may then be required, thus leading to an undesirable expansion effect. In this paper, we propose a method to detect adaptively the situations where the SI is of lower quality. Then puncturing matrices, enabling systematic bits, are used to help computing reliable channel likelihood ratios. An improvement up to 0.5 dB is reported for PSNRs vs bit rate performances.