| Summary: | With the popularity of video conferences, video calls and other activities, video transmission has been widely used. To meet a huge number of subscribers’ requirements, the mobile video transmission scheme needs to overcome some disadvantages, such as resources limitation and noise interference. The knowledge-enhanced mobile video broadcasting (KMV-Cast) is a scheme utilizing joint source-channel coding and correlated information in clouds. However, there is an item of noise that cannot be removed in the original KMV-Cast scheme. In this paper, an adaptive Wiener filtering denoising algorithm is proposed to reduce such noise at the receiver in order to maximize the signal-to-noise ratio (SNR) of the reconstructed video frame. The simulation results show that the proposed Wiener filter algorithm is superior to other schemes without the Wiener filter under different sources and channel qualities. At lower-SNR channels (i.e., −5dB), the proposed algorithm achieves 2dB gains in terms of peak signal-to-noise ratio (PSNR), while at higher-SNR channels (i.e., 10dB), the proposed algorithm achieves 3dB gains in terms of PSNR.
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