Practical estimation of adaptive correlation noise model for Distributed Video Coding

In contrast with the traditional video compression system, Distributed Video Coding (DVC) architecture dramatically shifts the complexity from the encoder to the decoder. This low-cost encoding concept can be exploited in the emerging applications, e.g. wireless sensor networks. In order to increase the compression efficiency, improvement of side information generation and refinements of Correlation Noise Model (CNM) are main streams to improve DVC. However, most of these schemes are theoretical and expensive for the decoder. In order to retain low-cost and efficient system, a side information refinement with a practical CNM estimation is proposed. While maintaining the video quality, our proposed mechanism totally improves the system compression efficiency about 18% for the bit-rate with a low complexity decoder.