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In this work, we propose a two-stage video coding framework, as an extensionof our previous one-stage framework in [1]. The two-stage frameworks consiststwo different dictionaries. Specifically, the first stage directly finds thesparse representation of a block with a self-adaptive dictionary consisting ofall possible inter-prediction candidates by solving an L0-norm minimizationproblem using an improved orthogonal matching pursuit with embeddedorthonormalization (eOMP) algorithm, and the second stage codes the residualusing DCT dictionary adaptively orthonormalized to the subspace spanned by thefirst stage atoms. The transition of the first stage and the second stage isdetermined based on both stages' quantization stepsizes and a threshold. Wefurther propose a complete context adaptive entropy coder to efficiently codethe locations and the coefficients of chosen first stage atoms. Simulationresults show that the proposed coder significantly improves the RD performanceover our previous one-stage coder. More importantly, the two-stage coder, usinga fixed block size and inter-prediction only, outperforms the H.264 coder(x264) and is competitive with the HEVC reference coder (HM) over a large raterange.

A two-stage video coding framework with both self-adaptive redundant dictionary and adaptively orthonormalized DCT basis