Optimal Viterbi Algorithm Based 3-D Total Variation Sequence Decoding (3-D TVSD) for Robust Video Reconstruction in Multimedia Wireless Sensor Networks

In this paper we propose an optimal scheme for robust reconstruction of the video stream transmitted in a multimedia wireless sensor network (MWSN). The proposed scheme is based on the principle of joint source-channel maximum likelihood (ML) and makes use of the bounded variation (BV) property of video signals in the space and time dimensions. The derived optimal joint source-channel decoder is a combination of the maximum likelihood cost function and an anisotropic total variation norm based regularization factor, which is well suited for the reconstruction of the video frames from the received symbol stream in a MWSN. Further we develop a novel trellis based Viterbi decoder with appropriate state and branch metrics which efficiently minimizes the TV cost function to yield the ML decoded video sequence. Simulation results are presented to illustrate the quality of video stream reconstruction in a MWSN and compare the performance of the proposed scheme with that of suboptimal conventional video decoding techniques.