Improved KMV-Cast with BM3D Denoising

Recently, a novel scheme called Knowledge-enhanced Mobile Video Broadcasting (KMV-Cast) was proposed to improve the quality of mobile video transmission. In this paper, we propose to use the well-known block-matching and three dimensional filtering (BM3D) algorithm to remove noise for KMV-Cast. BM3D is realized by block-matching, collaborative filtering, aggregation, and Wiener filtering. In this paper, BM3D will be used to remove noise after videos/images reconstruction using KMV-Cast receiver. The block-matching is used to collect similar pixel groups to reveal the property of the patch, while the collaborative filtering preserves the unique feature of each block through hard-thresholding. The aggregation process performs averaging to get the estimation results. The simulation results show that KMV-Cast with BM3D denoising performs the best compared with other two algorithms including SoftCast and KMV-Cast, especially in case of low channel quality and all image blocks are needed to be transmitted. The proposed scheme has 9 dB gains in terms of PSNR under low channel SNR (-5 dB) compared with the conventional KMV-Cast scheme, when all image blocks are transmitted through additive white Gaussian noise (AWGN) channel.