Improved Distributed Wyner-Ziv Video Coding Based On Reed Solomon Error Correction Scheme And Frame Estimation For Wireless Transmission - Chiam, Kin Honn (2015)
Recent years have witnessed the increase in demand for fast, efficient, and high quality communication of multimedia applications through the wireless and wired transmission. This has opened up the research area in distributed video coding (DVC) to flourish. The objectives of this thesis are to evaluate efficiency of implementation of different channel encoding schemes in DVC in protecting the source data in channel impairment environment and also reduce the number of frames transmission from the encoder. Most recently, the low density parity check codes (LDPC) are chosen to be the forward error correction technique to encode the Wyner-Ziv frames in DVC as the LDPC has more superior error correction performance than the turbo codes. However, the LDPC involves complicated encoding and decoding algorithm. In this thesis, the LDPC is replaced with the Reed Solomon (RS) codes to encode the Wyner-Ziv frames. Performance of RS codes in protecting source message is compared with the LDPC codes. As the RS codes involve less complicated encoding and decoding algorithm, the overall system time is reduced and the output is obtained in a shorter time. Based on the experiment results, the proposed model achieves a reduction of about 9.3% to 9.4 % in processing time, depending on the input video sequence, with acceptable quality of output video sequence. The RS codes are known for their capabilities to correct burst errors, which are common in fading channel. The second part of this thesis is the reduction of the number of frames transmission from the encoder. Only certain frames in the group of picture are transmitted from the encoder to reduce the overall transmission time of the system. The frames that are not transmitted shall be estimated at the decoder so that there will be a complete set of the group of picture at the decoder for the output video reconstruction. Based on the experiment results, the proposed model seems more effective and efficient as output video sequence could be obtained in a shorter time. The proposed model achieves a reduction of about 4.0% to 4.7 % in processing time, depending on the input video sequence. Moreover, the estimated output frames of the proposed model are also with acceptable quality as compared to the original input frames.