Three-dimensional subband coding techniques for wireless video communications

This paper presents a new 3-D subband coding framework that is able to achieve a good balance between high compression performance and channel error resilience. Various data transform methods for the decorrelation of video were examined and compared, including subband filtering, discrete cosine transforms, discrete wavelet transforms, and lapped transforms. The coding stage of the algorithm is based on a generalized adaptive quantization framework, which is applied to the 3-D transformed coefficients. More specifically, it features a simple coding structure based on quadtree coding and lattice vector quantization techniques. In typical applications, good performance at high compression ratios is obtained often without entropy coding. Furthermore, because temporal decorrelation is absorbed by the transform, traditional motion compensated prediction becomes not necessary, which results in a significant computational advantage over standard video coders. The error-resilience feature is achieved through classifying the compressed data streams into separated sub-streams with different error sensitivity levels. This enables a good adaptation to different channel models according to their noise statistics and error-protection protocols. Experimental results have shown that the subband video coder is able to achieve highly competitive performance relative to MPEG-2 in both noiseless and noisy environments. Furthermore, lapped transforms are shown experimentally to outperform the other transforms in the 3-D subband environment. The subband coding framework provides a practical solution for video communications over wireless channels, where efficiency, error resilience, and computational simplicity are vital in providing superior quality of service.