RESUMO
An uncoded transmission scheme called SoftCast has recently shown great potential for wireless video transmission. Unlike conventional approaches, SoftCast processes input images only by a series of transformations and modulates the coefficients directly to a dense constellation for transmission. The transmission is uncoded and lossy in nature, with its noise level commensurate with the channel condition. This paper presents a theoretical analysis for an uncoded visual communication, focusing on developing a quantitative measurements for the efficiency of decorrelation transform in a generalized uncoded transmission framework. Our analysis reveals that the energy distribution among signal elements is critical for the efficiency of uncoded transmission. A decorrelation transform can potentially bring a significant performance gain by boosting the energy diversity in signal representation. Numerical results on Markov random process and real image and video signals are reported to evaluate the performance gain of using different transforms in uncoded transmission. The analysis presented in this paper is verified by simulated SoftCast transmissions. This provide guidelines for designing efficient uncoded video transmission schemes.
RESUMO
Template matching (TM) was proposed in the literature a decade ago to efficiently remove non-local redundancies within an image without transmitting any overhead of displacement vectors. However, the large computational complexity introduced at both the encoder and the decoder, especially for a large search range, limits its widespread use. This paper proposes a hash-based line-by-line template matching (hLTM) for lossless screen image coding, where the non-local redundancy commonly exists in text and graphics parts. By hash-based search, it can largely reduce the search complexity of template matching without an accuracy degradation. Besides, the line-by-line template matching increases prediction accuracy by using a fine granularity. Experimental results show that the hLTM can significantly reduce both the encoding and decoding complexities by 68 and 23 times, respectively, compared with the traditional TM with a search radius of 128. Moreover, when compared with High Efficiency Video Coding screen content coding test model SCM-1.0, it can largely improve coding efficiency by up to 12.68% bits saving on screen contents with rich texts/graphics.
