Scalable Video Compression Framework With Adaptive Orientational Multiresolution Transform and Nonuniform Directional Filterbank Design
Although wavelet-based scalable video coding becomes the state-of-the-art video compression engine for its adaptability to heterogeneous networks and clients, a large number of attempts have been made to integrate local directionality onto discrete wavelet transform to explore the intrinsic geometrical structures. Taking into consideration that the contours and textures scattered in different scales change their directional resolutions as their curvatures change, we investigate adaptive directional resolutions along scales to achieve the dual (scale and orientation) multiresolution transform. This paper proposes nonuniform directional frequency decompositions for video representation and approximation, and exploits the nonuniformity of orientation multiresolution distribution and designs nonuniform directional filter banks to make the geometrical transform more sparse and efficient. The nonuniform directional frequency decomposition under arbitrary scales is fulfilled by a non-symmetric binary tree (NSBT) topology structure with nonuniform directional filterbank design. In turn, the proposed scalable video coding framework, called DMSVC, is enriched with the dual multiresolution transform. Each temporal subband through motion compensated temporal filtering is further decomposed into multiscale subbands, and the highpass wavelet subspaces are divided into an arbitrary number of directional subspaces in alignment with the orientation distribution via phase congruency to establish NSBT. The paraunitary perfect reconstruction condition is provided through a polyphase identical form of filter bank. Comparing with the isolated wavelet basis, our transform provides a greater correlated set of localized and anisotropic basis functions. The spatio-temporal subband coefficients are coded by a 3-D ESCOT entropy coding algorithm which is adopted to match the structure of NSBT. Experimental results show that the reconstructed video frames DMSVC in the proposed DMSVC scheme have better visual quality than existing scalable video coding schemes. It could produce higher compression ratio on video sequences full of directional edges and textures.