Performance Analysis of Transform in Uncoded Wireless Visual Communication

In wireless scenarios where the channel condition may vary drastically, visual communication systems using source and channel coding generally suffer from threshold effect. An uncoded transmission scheme called SoftCast [1]-[3], however, was recently shown to provide both graceful quality transition and competitive performance. In SoftCast, image signal is directly modulated to a dense constellation using proper power for transmission, solely after employing a transform for energy compaction, leaving out conventional quantization, entropy coding and channel coding. The received signal is lossy in nature, with its noise level commensurate with the channel condition. This paper presents a theoretical analysis for uncoded visual communication, focusing on the role of transform and the quantitative measurement of transform gain in a generalized uncoded transmission framework with optimal power allocation. Our analysis reveal that the energy distribution among signal elements plays an important role in the power- distortion performance. Further analysis show that the energy compaction capability of decorrelation transform can bring significant gain by boosting the energy diversity in signal representation. Numerical analysis results are reported for Markov random signals and natural images, respectively. The performance of typical transforms, e.g. KLT, DCT and DWT, and the effect of different transform sizes or levels are evaluated. These analysis results are verified by simulations.