Computationally efficient operational rate-distortion optimal SNR scalable codec

Abstract

We present a new scalable video codec which features a computationally efficient decoder as well as an operational rate-distortion optimal encoder. The SNR scalability is accomplished by splitting the Discrete Cosine Transform (DCT) coefficients of the Displaced Frame Difference (DFD) into groups that correspond to the scalable layers. Our Operational Rate-Distortion optimal scalable codec partitions the DCT coefficients of the DFD (or the intensity for intra blocks) into a base layer and one or more enhancement layers. The base layer is constructed by subtracting a value from each quantized DCT coefficient. The subtracted values are then sent as enhancement. If more than two scalable layers are required, the values subtracted for the creation of the base layer are further broken into other values. The partitioning of the DCT coefficients into layers is accomplished by formulating a constrained optimization problem which is then solved using lagrangian optimization. A Dynamic Programming (DP) solution is proposed in order to minimize the Lagrangian cost in a computationally efficient manner. We introduce a new method for finding the required Lagrangian multiplier λ which will meet our target bitrate. The method further reduces the computational complexity of the encoder by minimizing the need for an iterative calculation of the Lagrangian multiplier. Our experimental results show that the proposed codec typically outperforms H.263+ SNR scalability in terms of PSNR while exhibiting a low-complexity decoder. Due to the use of Dynamic Programming and a new method for the estimation of λ, the computational complexity of the operational rate-distortion optimal encoder is competitive with H.263+.